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DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260515T100000
DTEND;TZID=America/Detroit:20260515T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903485@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Professional Development,Research,Statistics,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260515T100000
DTEND;TZID=America/Detroit:20260515T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903466@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Health,Health And Retirement Study,Professional Development,Research,Science,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260515T130000
DTEND;TZID=America/Detroit:20260515T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903504@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Biomedical,Center For Political Studies,Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Graduate and Professional Students,Health,Health Data,Mathematics,Professional Development,Public Health,Research,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260515T130000
DTEND;TZID=America/Detroit:20260515T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903524@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260516T100000
DTEND;TZID=America/Detroit:20260516T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903486@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Professional Development,Research,Statistics,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260516T100000
DTEND;TZID=America/Detroit:20260516T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903467@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Health,Health And Retirement Study,Professional Development,Research,Science,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260516T130000
DTEND;TZID=America/Detroit:20260516T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903505@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Biomedical,Center For Political Studies,Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Graduate and Professional Students,Health,Health Data,Mathematics,Professional Development,Public Health,Research,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260516T130000
DTEND;TZID=America/Detroit:20260516T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903525@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260517T100000
DTEND;TZID=America/Detroit:20260517T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903487@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Professional Development,Research,Statistics,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260517T100000
DTEND;TZID=America/Detroit:20260517T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903468@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Health,Health And Retirement Study,Professional Development,Research,Science,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260517T130000
DTEND;TZID=America/Detroit:20260517T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903506@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Biomedical,Center For Political Studies,Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Graduate and Professional Students,Health,Health Data,Mathematics,Professional Development,Public Health,Research,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260517T130000
DTEND;TZID=America/Detroit:20260517T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903526@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260518T100000
DTEND;TZID=America/Detroit:20260518T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903488@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Professional Development,Research,Statistics,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260518T100000
DTEND;TZID=America/Detroit:20260518T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903469@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Health,Health And Retirement Study,Professional Development,Research,Science,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260518T130000
DTEND;TZID=America/Detroit:20260518T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903507@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Biomedical,Center For Political Studies,Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Graduate and Professional Students,Health,Health Data,Mathematics,Professional Development,Public Health,Research,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260518T130000
DTEND;TZID=America/Detroit:20260518T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903527@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260519T100000
DTEND;TZID=America/Detroit:20260519T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903489@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Professional Development,Research,Statistics,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260519T100000
DTEND;TZID=America/Detroit:20260519T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903470@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Health,Health And Retirement Study,Professional Development,Research,Science,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260519T130000
DTEND;TZID=America/Detroit:20260519T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903508@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Biomedical,Center For Political Studies,Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Graduate and Professional Students,Health,Health Data,Mathematics,Professional Development,Public Health,Research,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260519T130000
DTEND;TZID=America/Detroit:20260519T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903528@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260520T100000
DTEND;TZID=America/Detroit:20260520T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903490@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Professional Development,Research,Statistics,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260520T100000
DTEND;TZID=America/Detroit:20260520T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903463@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Health,Health And Retirement Study,Professional Development,Research,Science,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260520T100000
DTEND;TZID=America/Detroit:20260520T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903471@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Health,Health And Retirement Study,Professional Development,Research,Science,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260520T130000
DTEND;TZID=America/Detroit:20260520T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903509@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Biomedical,Center For Political Studies,Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Graduate and Professional Students,Health,Health Data,Mathematics,Professional Development,Public Health,Research,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260520T130000
DTEND;TZID=America/Detroit:20260520T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903529@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260521T100000
DTEND;TZID=America/Detroit:20260521T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903491@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Professional Development,Research,Statistics,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260521T100000
DTEND;TZID=America/Detroit:20260521T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903472@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Health,Health And Retirement Study,Professional Development,Research,Science,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260521T130000
DTEND;TZID=America/Detroit:20260521T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903510@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Biomedical,Center For Political Studies,Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Graduate and Professional Students,Health,Health Data,Mathematics,Professional Development,Public Health,Research,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260521T130000
DTEND;TZID=America/Detroit:20260521T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903530@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260522T100000
DTEND;TZID=America/Detroit:20260522T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903492@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Professional Development,Research,Statistics,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260522T100000
DTEND;TZID=America/Detroit:20260522T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903473@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Health,Health And Retirement Study,Professional Development,Research,Science,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260522T130000
DTEND;TZID=America/Detroit:20260522T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903511@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Biomedical,Center For Political Studies,Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Graduate and Professional Students,Health,Health Data,Mathematics,Professional Development,Public Health,Research,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260522T130000
DTEND;TZID=America/Detroit:20260522T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903531@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260523T100000
DTEND;TZID=America/Detroit:20260523T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903493@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Professional Development,Research,Statistics,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260523T100000
DTEND;TZID=America/Detroit:20260523T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903474@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Health,Health And Retirement Study,Professional Development,Research,Science,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260523T130000
DTEND;TZID=America/Detroit:20260523T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903512@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Biomedical,Center For Political Studies,Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Graduate and Professional Students,Health,Health Data,Mathematics,Professional Development,Public Health,Research,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260523T130000
DTEND;TZID=America/Detroit:20260523T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903532@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260524T100000
DTEND;TZID=America/Detroit:20260524T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903494@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Professional Development,Research,Statistics,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260524T100000
DTEND;TZID=America/Detroit:20260524T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903475@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Health,Health And Retirement Study,Professional Development,Research,Science,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260524T130000
DTEND;TZID=America/Detroit:20260524T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903513@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Biomedical,Center For Political Studies,Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Graduate and Professional Students,Health,Health Data,Mathematics,Professional Development,Public Health,Research,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260524T130000
DTEND;TZID=America/Detroit:20260524T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903533@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260525T100000
DTEND;TZID=America/Detroit:20260525T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903495@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Professional Development,Research,Statistics,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260525T100000
DTEND;TZID=America/Detroit:20260525T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903476@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Health,Health And Retirement Study,Professional Development,Research,Science,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260525T130000
DTEND;TZID=America/Detroit:20260525T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903514@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Biomedical,Center For Political Studies,Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Graduate and Professional Students,Health,Health Data,Mathematics,Professional Development,Public Health,Research,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260525T130000
DTEND;TZID=America/Detroit:20260525T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903534@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260526T100000
DTEND;TZID=America/Detroit:20260526T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903496@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Professional Development,Research,Statistics,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260526T100000
DTEND;TZID=America/Detroit:20260526T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903477@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Health,Health And Retirement Study,Professional Development,Research,Science,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260526T130000
DTEND;TZID=America/Detroit:20260526T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903515@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Biomedical,Center For Political Studies,Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Graduate and Professional Students,Health,Health Data,Mathematics,Professional Development,Public Health,Research,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260526T130000
DTEND;TZID=America/Detroit:20260526T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903535@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260527T100000
DTEND;TZID=America/Detroit:20260527T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903497@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Professional Development,Research,Statistics,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260527T100000
DTEND;TZID=America/Detroit:20260527T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903464@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Health,Health And Retirement Study,Professional Development,Research,Science,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260527T100000
DTEND;TZID=America/Detroit:20260527T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903478@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Health,Health And Retirement Study,Professional Development,Research,Science,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260527T130000
DTEND;TZID=America/Detroit:20260527T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903516@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Biomedical,Center For Political Studies,Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Graduate and Professional Students,Health,Health Data,Mathematics,Professional Development,Public Health,Research,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260527T130000
DTEND;TZID=America/Detroit:20260527T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903536@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260528T100000
DTEND;TZID=America/Detroit:20260528T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903498@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Professional Development,Research,Statistics,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260528T100000
DTEND;TZID=America/Detroit:20260528T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903479@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Health,Health And Retirement Study,Professional Development,Research,Science,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260528T130000
DTEND;TZID=America/Detroit:20260528T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903517@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Biomedical,Center For Political Studies,Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Graduate and Professional Students,Health,Health Data,Mathematics,Professional Development,Public Health,Research,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260528T130000
DTEND;TZID=America/Detroit:20260528T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903537@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260529T100000
DTEND;TZID=America/Detroit:20260529T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903499@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Professional Development,Research,Statistics,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260529T100000
DTEND;TZID=America/Detroit:20260529T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903480@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Health,Health And Retirement Study,Professional Development,Research,Science,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260529T130000
DTEND;TZID=America/Detroit:20260529T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903518@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Biomedical,Center For Political Studies,Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Graduate and Professional Students,Health,Health Data,Mathematics,Professional Development,Public Health,Research,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260529T130000
DTEND;TZID=America/Detroit:20260529T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903538@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260530T100000
DTEND;TZID=America/Detroit:20260530T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903500@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Professional Development,Research,Statistics,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260530T100000
DTEND;TZID=America/Detroit:20260530T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903481@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Health,Health And Retirement Study,Professional Development,Research,Science,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260530T130000
DTEND;TZID=America/Detroit:20260530T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903519@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Biomedical,Center For Political Studies,Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Graduate and Professional Students,Health,Health Data,Mathematics,Professional Development,Public Health,Research,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260530T130000
DTEND;TZID=America/Detroit:20260530T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903539@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260531T100000
DTEND;TZID=America/Detroit:20260531T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903501@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Professional Development,Research,Statistics,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260531T100000
DTEND;TZID=America/Detroit:20260531T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903482@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Health,Health And Retirement Study,Professional Development,Research,Science,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260531T130000
DTEND;TZID=America/Detroit:20260531T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903520@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Biomedical,Center For Political Studies,Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Graduate and Professional Students,Health,Health Data,Mathematics,Professional Development,Public Health,Research,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260531T130000
DTEND;TZID=America/Detroit:20260531T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903540@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260601T100000
DTEND;TZID=America/Detroit:20260601T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903502@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Professional Development,Research,Statistics,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260601T100000
DTEND;TZID=America/Detroit:20260601T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903483@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Health,Health And Retirement Study,Professional Development,Research,Science,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260601T130000
DTEND;TZID=America/Detroit:20260601T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903521@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Biomedical,Center For Political Studies,Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Graduate and Professional Students,Health,Health Data,Mathematics,Professional Development,Public Health,Research,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260601T130000
DTEND;TZID=America/Detroit:20260601T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903541@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260602T100000
DTEND;TZID=America/Detroit:20260602T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903601@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Professional Development,Research,Statistics,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260602T100000
DTEND;TZID=America/Detroit:20260602T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903614@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Health,Health And Retirement Study,Professional Development,Research,Science,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260602T130000
DTEND;TZID=America/Detroit:20260602T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903610@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Biomedical,Center For Political Studies,Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Graduate and Professional Students,Health,Health Data,Mathematics,Professional Development,Public Health,Research,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260602T130000
DTEND;TZID=America/Detroit:20260602T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903542@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260603T100000
DTEND;TZID=America/Detroit:20260603T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903602@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Professional Development,Research,Statistics,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260603T100000
DTEND;TZID=America/Detroit:20260603T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903615@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Health,Health And Retirement Study,Professional Development,Research,Science,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260603T130000
DTEND;TZID=America/Detroit:20260603T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903611@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Biomedical,Center For Political Studies,Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Graduate and Professional Students,Health,Health Data,Mathematics,Professional Development,Public Health,Research,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260603T130000
DTEND;TZID=America/Detroit:20260603T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903543@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260604T100000
DTEND;TZID=America/Detroit:20260604T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903603@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Professional Development,Research,Statistics,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260604T100000
DTEND;TZID=America/Detroit:20260604T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903616@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Health,Health And Retirement Study,Professional Development,Research,Science,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260604T130000
DTEND;TZID=America/Detroit:20260604T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903612@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Biomedical,Center For Political Studies,Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Graduate and Professional Students,Health,Health Data,Mathematics,Professional Development,Public Health,Research,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260604T130000
DTEND;TZID=America/Detroit:20260604T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903544@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260605T100000
DTEND;TZID=America/Detroit:20260605T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903604@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Professional Development,Research,Statistics,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131309
DTSTART;TZID=America/Detroit:20260605T100000
DTEND;TZID=America/Detroit:20260605T150000
SUMMARY:Class / Instruction:June 1-5\, 2026 Course - Introduction to the Health and Retirement Study (HRS) Workshop
DESCRIPTION:June 1-5\, 2026 M-F\n10:00am - $3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nIntroduction to the Health and Retirement Study (HRS) Workshop\n\nThe Health and Retirement Study (hrs.isr.umich.edu) workshop is intended to give participants an introduction to the study that will enable them to get started using the data for research. HRS is a large-scale longitudinal study with more than 20 years of data on the labor force participation and health transitions that individuals undergo toward the end of their work lives and in the years that follow. This online workshop is intended for users who have little to no experience using HRS data.\n\nContent lectures delivered by HRS co-investigators and content area experts on basic survey content\, sample design\, weighting\, and restricted data files will be available on the course website for viewing ahead of time. During the week of the workshop\, each content lecturer will participate in a Zoom meeting with the class to answer questions about their lecture. The majority of each day will be devoted to data labs in which participants will gain experience using the data\, with a strong focus on introductory data management and simple data analysis.\n\nAmanda Sonnega\, PhD\, is a Research Scientist in the Survey Research Center of the Institute for Social Research (ISR) at the University of Michigan (UM)\, where she is responsible for integrating communication\, outreach\, and education efforts for the Health and Retirement Study. She received her doctorate through the Department of Health\, Behavior\, and Society at the Johns Hopkins University and completed a postdoctoral fellowship within the ISR program in Social Environment and Health. Dr. Sonnega has lectured in the UM School of Public Health on psychosocial factors in health-related behavior. Her research focuses on life course trajectories of physical and mental health\; institutional and personal factors associated with vulnerability and resilience in aging individuals\; and work transitions and their broad effects on health and well-being.
UID:148257-21903617@events.umich.edu
URL:https://events.umich.edu/event/148257
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Health,Health And Retirement Study,Professional Development,Research,Science,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260605T130000
DTEND;TZID=America/Detroit:20260605T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903613@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Biomedical,Center For Political Studies,Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Graduate and Professional Students,Health,Health Data,Mathematics,Professional Development,Public Health,Research,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260605T130000
DTEND;TZID=America/Detroit:20260605T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903545@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260606T100000
DTEND;TZID=America/Detroit:20260606T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903605@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Professional Development,Research,Statistics,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260606T130000
DTEND;TZID=America/Detroit:20260606T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903546@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260607T100000
DTEND;TZID=America/Detroit:20260607T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903606@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Professional Development,Research,Statistics,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260607T130000
DTEND;TZID=America/Detroit:20260607T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903547@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260608T100000
DTEND;TZID=America/Detroit:20260608T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903607@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Professional Development,Research,Statistics,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260608T130000
DTEND;TZID=America/Detroit:20260608T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903548@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260609T100000
DTEND;TZID=America/Detroit:20260609T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903608@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Professional Development,Research,Statistics,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260609T130000
DTEND;TZID=America/Detroit:20260609T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903549@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130858
DTSTART;TZID=America/Detroit:20260610T100000
DTEND;TZID=America/Detroit:20260610T130000
SUMMARY:Class / Instruction:June 1-10\, 2026  MWF Course - Data Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences
DESCRIPTION:June 1-10\, 2026  MWF\n10:00am - 1:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course. \n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nData Collection Using Wearables\, Sensors\, and Apps in the Social\, Behavioral\, and Health Sciences\n\nThe recent proliferation of mobile technology allows researchers to collect objective health and behavioral data at increased intervals\, in real time\, and may also reduce participant burden. In this course\, we will provide examples of the utility of and integration of wearables\, sensors\, and apps in research settings. Examples will include the use of wearable health devices to measure activity\, apps for ecological momentary assessment\, and smartphone sensors to measure sound and movement\, among others. Additionally\, this course will consider the integration of these new technologies into existing surveys and the quality of the data collected from the total survey error perspective. We will discuss considerations for assessing coverage\, participation\, and measurement error when integrating wearables\, sensors\, and apps in a research setting as well as the costs and privacy considerations when collecting these types of data. Participants will work in groups to discuss a research study design using new technology and have the opportunity for hands-on practice with sensor data.\n\nHeidi Guyer is Senior Public Health Research Scientist at RTI International. Before joining RTI\, she was a Senior Survey Director and oversaw data collection on large national and international health research projects at the University of Michigan. She received a PhD in Epidemiology from the University of Michigan and a Master of Public Health from the University of Texas. She has extensive experience in population-based data collection\, cross-sectional and longitudinal health surveys\, and adapting clinical measures and new technology in health research. Her substantive areas of research have focused on the association between health behaviors\, such as sleep and diet quality\, and the development of chronic health conditions.
UID:148256-21903609@events.umich.edu
URL:https://events.umich.edu/event/148256
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Professional Development,Research,Statistics,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260610T130000
DTEND;TZID=America/Detroit:20260610T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903550@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260611T130000
DTEND;TZID=America/Detroit:20260611T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903551@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260612T130000
DTEND;TZID=America/Detroit:20260612T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903552@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260613T130000
DTEND;TZID=America/Detroit:20260613T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903553@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260614T130000
DTEND;TZID=America/Detroit:20260614T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903554@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260615T130000
DTEND;TZID=America/Detroit:20260615T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903555@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260616T130000
DTEND;TZID=America/Detroit:20260616T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903556@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260617T130000
DTEND;TZID=America/Detroit:20260617T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903557@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260618T130000
DTEND;TZID=America/Detroit:20260618T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903558@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260619T130000
DTEND;TZID=America/Detroit:20260619T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903559@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260620T130000
DTEND;TZID=America/Detroit:20260620T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903560@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260621T130000
DTEND;TZID=America/Detroit:20260621T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903561@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260622T130000
DTEND;TZID=America/Detroit:20260622T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903562@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260623T130000
DTEND;TZID=America/Detroit:20260623T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903563@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260624T130000
DTEND;TZID=America/Detroit:20260624T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903564@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260625T130000
DTEND;TZID=America/Detroit:20260625T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903565@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260626T130000
DTEND;TZID=America/Detroit:20260626T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903566@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260627T130000
DTEND;TZID=America/Detroit:20260627T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903567@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260628T130000
DTEND;TZID=America/Detroit:20260628T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903568@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260629T130000
DTEND;TZID=America/Detroit:20260629T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903569@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260630T130000
DTEND;TZID=America/Detroit:20260630T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903570@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260701T130000
DTEND;TZID=America/Detroit:20260701T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903571@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260702T130000
DTEND;TZID=America/Detroit:20260702T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903572@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260703T130000
DTEND;TZID=America/Detroit:20260703T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903573@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260704T130000
DTEND;TZID=America/Detroit:20260704T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903574@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260705T130000
DTEND;TZID=America/Detroit:20260705T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903575@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260706T130000
DTEND;TZID=America/Detroit:20260706T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903576@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260707T130000
DTEND;TZID=America/Detroit:20260707T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903577@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260708T130000
DTEND;TZID=America/Detroit:20260708T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903578@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260709T130000
DTEND;TZID=America/Detroit:20260709T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903579@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260710T130000
DTEND;TZID=America/Detroit:20260710T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903580@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260711T130000
DTEND;TZID=America/Detroit:20260711T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903581@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260712T130000
DTEND;TZID=America/Detroit:20260712T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903582@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260713T130000
DTEND;TZID=America/Detroit:20260713T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903583@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260714T130000
DTEND;TZID=America/Detroit:20260714T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903584@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260715T130000
DTEND;TZID=America/Detroit:20260715T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903585@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260716T130000
DTEND;TZID=America/Detroit:20260716T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903586@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260717T130000
DTEND;TZID=America/Detroit:20260717T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903587@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260718T130000
DTEND;TZID=America/Detroit:20260718T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903588@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260719T130000
DTEND;TZID=America/Detroit:20260719T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903589@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260720T130000
DTEND;TZID=America/Detroit:20260720T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903590@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260721T130000
DTEND;TZID=America/Detroit:20260721T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903591@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260722T130000
DTEND;TZID=America/Detroit:20260722T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903592@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260723T130000
DTEND;TZID=America/Detroit:20260723T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903593@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260724T130000
DTEND;TZID=America/Detroit:20260724T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903594@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260725T130000
DTEND;TZID=America/Detroit:20260725T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903595@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260726T130000
DTEND;TZID=America/Detroit:20260726T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903596@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260727T130000
DTEND;TZID=America/Detroit:20260727T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903597@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260728T130000
DTEND;TZID=America/Detroit:20260728T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903598@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260729T130000
DTEND;TZID=America/Detroit:20260729T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903599@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260730T130000
DTEND;TZID=America/Detroit:20260730T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903600@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
END:VEVENT
END:VCALENDAR