BEGIN:VCALENDAR VERSION:2.0 PRODID:-//UM//UM*Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:America/Detroit TZURL:http://tzurl.org/zoneinfo/America/Detroit X-LIC-LOCATION:America/Detroit BEGIN:DAYLIGHT TZOFFSETFROM:-0500 TZOFFSETTO:-0400 TZNAME:EDT DTSTART:20070311T020000 RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=2SU END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:EST DTSTART:20071104T020000 RRULE:FREQ=YEARLY;BYMONTH=11;BYDAY=1SU END:STANDARD END:VTIMEZONE 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:20260610T135252 DTSTART;TZID=America/Detroit:20260707T090000 DTEND;TZID=America/Detroit:20260707T160000 SUMMARY:Class / Instruction:Noncredit short courses presented by the Summer Institute in Survey Research Techniques DESCRIPTION:Founded 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\nClasses are open for registration.\nYou do not have to be affiliated with the University to attend. \nRegistration and payment are required a minimum of two weeks prior to the start of the class. \n\nJuly 7 and 9\, 2026 (T/Th)\n9:00am-1:00pm\nInterventions in a Responsive Survey Design Framework\nPresented by Brady T. West\nCourse Fee: $600\n\nJuly 13-17\, 2026 (M-F)\n1:00pm-4:00pm\nDesigning and Writing Questions for Surveys: Guidelines and Recommendations\nPresented by Jennifer (Jen) Dykema\nCourse Fee: $1\,200\n\nJuly 13-17\, 2026 (M-F)\n10:30am-12:00pm\nIntegrating Qualitative Methods into Survey Research\nPresented by Darby Steiger\nCourse Fee: $500\n\nJuly 20-23\, 2026 (M-Th)\n12:00pm-4:00pm\nGoing Deeper into Questionnaire Design with Alternative Methods and Tools\nPresented by Pamela Campanelli\nCourse Fee: $1\,200\n\nJuly 20-30\, 2026 (M T TH: Live instruction\; W: Video instruction)\n10:00am-11:30am\nNatural Language Processing with R\nPresented by Robyn Ferg\nCourse Fee: $1\,200 UID:148807-21904750@events.umich.edu URL:https://events.umich.edu/event/148807 CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Bias,Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate and Professional Students,Lecture,Mathematics,Research,Social Science,Social Sciences,Statistics,Survey Methodology,Survey Methods,Survey Research LOCATION:Off Campus Location CONTACT: END:VEVENT BEGIN:VEVENT DTSTAMP:20260610T140610 DTSTART;TZID=America/Detroit:20260707T090000 DTEND;TZID=America/Detroit:20260707T130000 SUMMARY:Class / Instruction:Interventions in a Responsive Survey Design Framework DESCRIPTION:Founded 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\nClasses are open for registration.\nYou do not have to be affiliated with the University to attend. \nRegistration and payment are required a minimum of two weeks prior to the start of the class. \n\nJuly 7 and 9\, 2026 (T/Th)\n9:00am-1:00pm\nInterventions in a Responsive Survey Design Framework\nPresented by Brady T. West\nCourse Fee: $600\n\nThis course focuses on the implementation of potential interventions within a responsive survey design (RSD) framework. Many of these interventions have been tested experimentally\, and the course will examine evaluations of those experiments to highlight their effectiveness. Emphasis will be placed on the role of experimental evaluation in the early early stages of RSD. This course will also cover practical methods for implementing interventions\, including the design and execution of experiments to assess new approaches. In addition\, strategies for applying these interventions in both interviewer-mediated and self-administered surveys (e.g.\, web and mail) will be discussed.\n\nBrady T. West is a Research Professor in the Michigan Program in Survey and Data Science\, located within the Survey Research Center at the Institute for Social Research on the University of Michigan-Ann Arbor (U-M) campus. He earned his PhD from the Michigan Program in Survey Methodology in 2011. Before that\, he received an MA in Applied Statistics from the U-M Statistics Department in 2002\, being recognized as an Outstanding First-year Applied Masters student\, and a BS in Statistics with Highest Honors and Highest Distinction from the U-M Statistics Department in 2001. His current research interests include the implications of measurement error in auxiliary variables and survey paradata for survey estimation\, selection bias in surveys\, adaptive and responsive survey design\, interviewer effects\, and multilevel regression models for clustered and longitudinal data. He is the lead author of a book comparing different statistical software packages in terms of their mixed-effects modeling procedures (Linear Mixed Models: A Practical Guide using Statistical Software\, Third Edition\, Chapman Hall/CRC Press\, 2022)\, and he is a co-author of a second book entitled Applied Survey Data Analysis (with Steven Heeringa and Pat Berglund)\, the second edition of which was published by Chapman Hill in June 2017. He was elected as a Fellow of the American Statistical Association in 2022. UID:148809-21904775@events.umich.edu URL:https://events.umich.edu/event/148809 CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate and Professional Students,Mathematics,Research,Science,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:20260610T135252 DTSTART;TZID=America/Detroit:20260708T090000 DTEND;TZID=America/Detroit:20260708T160000 SUMMARY:Class / Instruction:Noncredit short courses presented by the Summer Institute in Survey Research Techniques DESCRIPTION:Founded 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\nClasses are open for registration.\nYou do not have to be affiliated with the University to attend. \nRegistration and payment are required a minimum of two weeks prior to the start of the class. \n\nJuly 7 and 9\, 2026 (T/Th)\n9:00am-1:00pm\nInterventions in a Responsive Survey Design Framework\nPresented by Brady T. West\nCourse Fee: $600\n\nJuly 13-17\, 2026 (M-F)\n1:00pm-4:00pm\nDesigning and Writing Questions for Surveys: Guidelines and Recommendations\nPresented by Jennifer (Jen) Dykema\nCourse Fee: $1\,200\n\nJuly 13-17\, 2026 (M-F)\n10:30am-12:00pm\nIntegrating Qualitative Methods into Survey Research\nPresented by Darby Steiger\nCourse Fee: $500\n\nJuly 20-23\, 2026 (M-Th)\n12:00pm-4:00pm\nGoing Deeper into Questionnaire Design with Alternative Methods and Tools\nPresented by Pamela Campanelli\nCourse Fee: $1\,200\n\nJuly 20-30\, 2026 (M T TH: Live instruction\; W: Video instruction)\n10:00am-11:30am\nNatural Language Processing with R\nPresented by Robyn Ferg\nCourse Fee: $1\,200 UID:148807-21904752@events.umich.edu URL:https://events.umich.edu/event/148807 CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Bias,Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate and Professional Students,Lecture,Mathematics,Research,Social Science,Social Sciences,Statistics,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:20260610T135252 DTSTART;TZID=America/Detroit:20260709T090000 DTEND;TZID=America/Detroit:20260709T160000 SUMMARY:Class / Instruction:Noncredit short courses presented by the Summer Institute in Survey Research Techniques DESCRIPTION:Founded 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\nClasses are open for registration.\nYou do not have to be affiliated with the University to attend. \nRegistration and payment are required a minimum of two weeks prior to the start of the class. \n\nJuly 7 and 9\, 2026 (T/Th)\n9:00am-1:00pm\nInterventions in a Responsive Survey Design Framework\nPresented by Brady T. West\nCourse Fee: $600\n\nJuly 13-17\, 2026 (M-F)\n1:00pm-4:00pm\nDesigning and Writing Questions for Surveys: Guidelines and Recommendations\nPresented by Jennifer (Jen) Dykema\nCourse Fee: $1\,200\n\nJuly 13-17\, 2026 (M-F)\n10:30am-12:00pm\nIntegrating Qualitative Methods into Survey Research\nPresented by Darby Steiger\nCourse Fee: $500\n\nJuly 20-23\, 2026 (M-Th)\n12:00pm-4:00pm\nGoing Deeper into Questionnaire Design with Alternative Methods and Tools\nPresented by Pamela Campanelli\nCourse Fee: $1\,200\n\nJuly 20-30\, 2026 (M T TH: Live instruction\; W: Video instruction)\n10:00am-11:30am\nNatural Language Processing with R\nPresented by Robyn Ferg\nCourse Fee: $1\,200 UID:148807-21904753@events.umich.edu URL:https://events.umich.edu/event/148807 CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Bias,Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate and Professional Students,Lecture,Mathematics,Research,Social Science,Social Sciences,Statistics,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:20260610T140610 DTSTART;TZID=America/Detroit:20260709T140000 DTEND;TZID=America/Detroit:20260709T150000 SUMMARY:Class / Instruction:Interventions in a Responsive Survey Design Framework DESCRIPTION:Founded 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\nClasses are open for registration.\nYou do not have to be affiliated with the University to attend. \nRegistration and payment are required a minimum of two weeks prior to the start of the class. \n\nJuly 7 and 9\, 2026 (T/Th)\n9:00am-1:00pm\nInterventions in a Responsive Survey Design Framework\nPresented by Brady T. West\nCourse Fee: $600\n\nThis course focuses on the implementation of potential interventions within a responsive survey design (RSD) framework. Many of these interventions have been tested experimentally\, and the course will examine evaluations of those experiments to highlight their effectiveness. Emphasis will be placed on the role of experimental evaluation in the early early stages of RSD. This course will also cover practical methods for implementing interventions\, including the design and execution of experiments to assess new approaches. In addition\, strategies for applying these interventions in both interviewer-mediated and self-administered surveys (e.g.\, web and mail) will be discussed.\n\nBrady T. West is a Research Professor in the Michigan Program in Survey and Data Science\, located within the Survey Research Center at the Institute for Social Research on the University of Michigan-Ann Arbor (U-M) campus. He earned his PhD from the Michigan Program in Survey Methodology in 2011. Before that\, he received an MA in Applied Statistics from the U-M Statistics Department in 2002\, being recognized as an Outstanding First-year Applied Masters student\, and a BS in Statistics with Highest Honors and Highest Distinction from the U-M Statistics Department in 2001. His current research interests include the implications of measurement error in auxiliary variables and survey paradata for survey estimation\, selection bias in surveys\, adaptive and responsive survey design\, interviewer effects\, and multilevel regression models for clustered and longitudinal data. He is the lead author of a book comparing different statistical software packages in terms of their mixed-effects modeling procedures (Linear Mixed Models: A Practical Guide using Statistical Software\, Third Edition\, Chapman Hall/CRC Press\, 2022)\, and he is a co-author of a second book entitled Applied Survey Data Analysis (with Steven Heeringa and Pat Berglund)\, the second edition of which was published by Chapman Hill in June 2017. He was elected as a Fellow of the American Statistical Association in 2022. UID:148809-21904776@events.umich.edu URL:https://events.umich.edu/event/148809 CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate and Professional Students,Mathematics,Research,Science,Survey Methodology,Survey Methods,Survey Research LOCATION:Off Campus Location CONTACT: END:VEVENT BEGIN:VEVENT DTSTAMP:20260610T135252 DTSTART;TZID=America/Detroit:20260710T090000 DTEND;TZID=America/Detroit:20260710T160000 SUMMARY:Class / Instruction:Noncredit short courses presented by the Summer Institute in Survey Research Techniques DESCRIPTION:Founded 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\nClasses are open for registration.\nYou do not have to be affiliated with the University to attend. \nRegistration and payment are required a minimum of two weeks prior to the start of the class. \n\nJuly 7 and 9\, 2026 (T/Th)\n9:00am-1:00pm\nInterventions in a Responsive Survey Design Framework\nPresented by Brady T. West\nCourse Fee: $600\n\nJuly 13-17\, 2026 (M-F)\n1:00pm-4:00pm\nDesigning and Writing Questions for Surveys: Guidelines and Recommendations\nPresented by Jennifer (Jen) Dykema\nCourse Fee: $1\,200\n\nJuly 13-17\, 2026 (M-F)\n10:30am-12:00pm\nIntegrating Qualitative Methods into Survey Research\nPresented by Darby Steiger\nCourse Fee: $500\n\nJuly 20-23\, 2026 (M-Th)\n12:00pm-4:00pm\nGoing Deeper into Questionnaire Design with Alternative Methods and Tools\nPresented by Pamela Campanelli\nCourse Fee: $1\,200\n\nJuly 20-30\, 2026 (M T TH: Live instruction\; W: Video instruction)\n10:00am-11:30am\nNatural Language Processing with R\nPresented by Robyn Ferg\nCourse Fee: $1\,200 UID:148807-21904754@events.umich.edu URL:https://events.umich.edu/event/148807 CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Bias,Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate and Professional Students,Lecture,Mathematics,Research,Social Science,Social Sciences,Statistics,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:20260610T135252 DTSTART;TZID=America/Detroit:20260713T090000 DTEND;TZID=America/Detroit:20260713T160000 SUMMARY:Class / Instruction:Noncredit short courses presented by the Summer Institute in Survey Research Techniques DESCRIPTION:Founded 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\nClasses are open for registration.\nYou do not have to be affiliated with the University to attend. \nRegistration and payment are required a minimum of two weeks prior to the start of the class. \n\nJuly 7 and 9\, 2026 (T/Th)\n9:00am-1:00pm\nInterventions in a Responsive Survey Design Framework\nPresented by Brady T. West\nCourse Fee: $600\n\nJuly 13-17\, 2026 (M-F)\n1:00pm-4:00pm\nDesigning and Writing Questions for Surveys: Guidelines and Recommendations\nPresented by Jennifer (Jen) Dykema\nCourse Fee: $1\,200\n\nJuly 13-17\, 2026 (M-F)\n10:30am-12:00pm\nIntegrating Qualitative Methods into Survey Research\nPresented by Darby Steiger\nCourse Fee: $500\n\nJuly 20-23\, 2026 (M-Th)\n12:00pm-4:00pm\nGoing Deeper into Questionnaire Design with Alternative Methods and Tools\nPresented by Pamela Campanelli\nCourse Fee: $1\,200\n\nJuly 20-30\, 2026 (M T TH: Live instruction\; W: Video instruction)\n10:00am-11:30am\nNatural Language Processing with R\nPresented by Robyn Ferg\nCourse Fee: $1\,200 UID:148807-21904757@events.umich.edu URL:https://events.umich.edu/event/148807 CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Bias,Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate and Professional Students,Lecture,Mathematics,Research,Social Science,Social Sciences,Statistics,Survey Methodology,Survey Methods,Survey Research LOCATION:Off Campus Location CONTACT: END:VEVENT BEGIN:VEVENT DTSTAMP:20260610T143232 DTSTART;TZID=America/Detroit:20260713T103000 DTEND;TZID=America/Detroit:20260713T120000 SUMMARY:Class / Instruction:Integrating Qualitative Methods into Survey Research DESCRIPTION:Founded 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\nClasses are open for registration.\nYou do not have to be affiliated with the University to attend. \nRegistration and payment are required a minimum of two weeks prior to the start of the class. \n\nJuly 13-17\, 2026 (M-F)\n10:30am-12:00pm\nIntegrating Qualitative Methods into Survey Research\nPresented by Darby Steiger\nCourse Fee: $500\n\nThis intensive course is designed to introduce novice and intermediate survey researchers to the integration of qualitative methods into survey research. Guided by the literature on mixed methods research\, the course will present various motivations and strategies for blending qualitative components into a quantitative study. Students will be introduced to a variety of qualitative methods and the ways each approach can complement a survey\, including focus groups\, in-depth interviews\, asynchronous research\, cognitive testing\, open-ended survey questions\, and multiple methods used across a single study. Through case studies and collaborative exercises\, students will explore the potential contribution of each method\, as well as the benefits of combined methods to advance and understand specific research questions. Practical considerations will be covered\, including study design\, sampling\, recruitment\, data collection\, analysis\, and integration of qualitative findings into survey reporting. This course is designed for those with a specific research question in mind\, as participants will be asked to design multi-method approaches to a research question of their choice. By the end of this course\, participants will understand the role qualitative research can play in survey research and how to design and implement a qualitative phase in a multimethod study.\n\nDarby Steiger is Vice President of Innovation & Solutions and Director of Qualitative Research at SSRS. Darby is responsible for spearheading the advancement of the core SSRS research products while driving cutting-edge approaches to the firm’s qualitative and quantitative research divisions. With over 30 years as a qualitative researcher and survey methodologist\, Darby has extensive experience conducting qualitative and quantitative research for a wide range of organizations and topics. A national leader in research methods\, Darby regularly presents at leading industry conferences and recently served on the Executive Council of the American Association for Public Opinion Research. Darby has three degrees from the University of Michigan. UID:148811-21904782@events.umich.edu URL:https://events.umich.edu/event/148811 CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate and Professional Students,Mathematics,Online,Research,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:20260610T141904 DTSTART;TZID=America/Detroit:20260713T130000 DTEND;TZID=America/Detroit:20260713T160000 SUMMARY:Class / Instruction:Designing and Writing Questions for Surveys: Guidelines and Recommendations DESCRIPTION:Founded 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\nClasses are open for registration.\nYou do not have to be affiliated with the University to attend. \nRegistration and payment are required a minimum of two weeks prior to the start of the class. \n\nJuly 13-17\, 2026 (M-F)\n1:00pm-4:00pm\nDesigning and Writing Questions for Surveys: Guidelines and Recommendations\nPresented by Jennifer (Jen) Dykema\nCourse Fee: $1\,200\n\nThis workshop distills research about survey questions to principles that can be applied to write survey questions that are clear and obtain reliable answers. The workshop provides students with tools to use in diagnosing problems in survey questions and in writing their own survey questions. Sessions combine lectures with group exercises & discussion. The lecture provides guidelines for writing and revising survey questions and illustrates how to revise troubled questions. Sessions consider both questions about events and behaviors and questions about subjective phenomena (such as attitudes\, evaluations\, and internal states).\n\nCOURSE OBJECTIVES\n\nIntroduce a structural analysis of parts of a survey question. Describe guidelines for diagnosing problems in survey questions and writing new survey questions. Focus on the structure and wording of survey questions\, whether for interviewer-administered or self-administered instruments. Provide an opportunity to apply the guidelines and principles during in-class exercises. Focus on improving individual questions and sets of questions. Summarize research that underlies key decisions in writing survey questions. Introduce cognitive interviewing as a method for testing survey questions.\n\nWHO SHOULD ATTEND\n\nIndividuals who will be writing or reviewing survey questions or survey instruments or analyzing survey data. This course gives practical guidance to those who have written survey questions but who are not familiar with the research on question design\, those who are just beginning to design survey instruments\, and those who use survey data but do not themselves design survey instruments.\n\nINSTRUCTOR\n\nJennifer (Jen) Dykema s an Professor of Sociology and the Faculty Director of the University of Wisconsin Survey Center (UWSC). Jen’s research focuses on survey methodology\, identifying sources of errors produced in the process of gathering standardized measurements and developing and implementing methods to reduce those errors. This work examines three main areas of inquiry: questionnaire design\, methods to increase response rates\, and interviewer-respondent interaction. As Faculty Director\, Jen oversees a program of methodological research that incorporates experiments and evaluations in ongoing projects. Her research has appeared in a number of journals including Public Opinion Quarterly\, Journal of Survey Statistics and Methodology\, Social Science Computer Review\, and Field Methods\, and edited volumes including the Handbook of Survey Research and Advances in Questionnaire Design\, Development\, Evaluation and Testing. She recently co-edited “Interviewer Effects from a Total Survey Error Perspective (2020).” Jen served as the Conference Chair for the American Association for Public Opinion Research (AAPOR) in 2017\, and in 2022 she was selected as a Fellow of the Midwest Association for Public Opinion Research (MAPOR). Jen earned her B.A. in psychology and sociology from the University of Michigan\, and her M.S. and Ph.D. in sociology from the University of Wisconsin-Madison. UID:148810-21904777@events.umich.edu URL:https://events.umich.edu/event/148810 CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate and Professional Students,Mathematics,Survey Methodology,Survey Methods,Survey Research LOCATION:Off Campus Location CONTACT: END:VEVENT BEGIN:VEVENT DTSTAMP:20260610T135252 DTSTART;TZID=America/Detroit:20260714T090000 DTEND;TZID=America/Detroit:20260714T160000 SUMMARY:Class / Instruction:Noncredit short courses presented by the Summer Institute in Survey Research Techniques DESCRIPTION:Founded 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\nClasses are open for registration.\nYou do not have to be affiliated with the University to attend. \nRegistration and payment are required a minimum of two weeks prior to the start of the class. \n\nJuly 7 and 9\, 2026 (T/Th)\n9:00am-1:00pm\nInterventions in a Responsive Survey Design Framework\nPresented by Brady T. West\nCourse Fee: $600\n\nJuly 13-17\, 2026 (M-F)\n1:00pm-4:00pm\nDesigning and Writing Questions for Surveys: Guidelines and Recommendations\nPresented by Jennifer (Jen) Dykema\nCourse Fee: $1\,200\n\nJuly 13-17\, 2026 (M-F)\n10:30am-12:00pm\nIntegrating Qualitative Methods into Survey Research\nPresented by Darby Steiger\nCourse Fee: $500\n\nJuly 20-23\, 2026 (M-Th)\n12:00pm-4:00pm\nGoing Deeper into Questionnaire Design with Alternative Methods and Tools\nPresented by Pamela Campanelli\nCourse Fee: $1\,200\n\nJuly 20-30\, 2026 (M T TH: Live instruction\; W: Video instruction)\n10:00am-11:30am\nNatural Language Processing with R\nPresented by Robyn Ferg\nCourse Fee: $1\,200 UID:148807-21904758@events.umich.edu URL:https://events.umich.edu/event/148807 CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Bias,Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate and Professional Students,Lecture,Mathematics,Research,Social Science,Social Sciences,Statistics,Survey Methodology,Survey Methods,Survey Research LOCATION:Off Campus Location CONTACT: END:VEVENT BEGIN:VEVENT DTSTAMP:20260610T143232 DTSTART;TZID=America/Detroit:20260714T103000 DTEND;TZID=America/Detroit:20260714T120000 SUMMARY:Class / Instruction:Integrating Qualitative Methods into Survey Research DESCRIPTION:Founded 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\nClasses are open for registration.\nYou do not have to be affiliated with the University to attend. \nRegistration and payment are required a minimum of two weeks prior to the start of the class. \n\nJuly 13-17\, 2026 (M-F)\n10:30am-12:00pm\nIntegrating Qualitative Methods into Survey Research\nPresented by Darby Steiger\nCourse Fee: $500\n\nThis intensive course is designed to introduce novice and intermediate survey researchers to the integration of qualitative methods into survey research. Guided by the literature on mixed methods research\, the course will present various motivations and strategies for blending qualitative components into a quantitative study. Students will be introduced to a variety of qualitative methods and the ways each approach can complement a survey\, including focus groups\, in-depth interviews\, asynchronous research\, cognitive testing\, open-ended survey questions\, and multiple methods used across a single study. Through case studies and collaborative exercises\, students will explore the potential contribution of each method\, as well as the benefits of combined methods to advance and understand specific research questions. Practical considerations will be covered\, including study design\, sampling\, recruitment\, data collection\, analysis\, and integration of qualitative findings into survey reporting. This course is designed for those with a specific research question in mind\, as participants will be asked to design multi-method approaches to a research question of their choice. By the end of this course\, participants will understand the role qualitative research can play in survey research and how to design and implement a qualitative phase in a multimethod study.\n\nDarby Steiger is Vice President of Innovation & Solutions and Director of Qualitative Research at SSRS. Darby is responsible for spearheading the advancement of the core SSRS research products while driving cutting-edge approaches to the firm’s qualitative and quantitative research divisions. With over 30 years as a qualitative researcher and survey methodologist\, Darby has extensive experience conducting qualitative and quantitative research for a wide range of organizations and topics. A national leader in research methods\, Darby regularly presents at leading industry conferences and recently served on the Executive Council of the American Association for Public Opinion Research. Darby has three degrees from the University of Michigan. UID:148811-21904783@events.umich.edu URL:https://events.umich.edu/event/148811 CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate and Professional Students,Mathematics,Online,Research,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:20260610T141904 DTSTART;TZID=America/Detroit:20260714T130000 DTEND;TZID=America/Detroit:20260714T160000 SUMMARY:Class / Instruction:Designing and Writing Questions for Surveys: Guidelines and Recommendations DESCRIPTION:Founded 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\nClasses are open for registration.\nYou do not have to be affiliated with the University to attend. \nRegistration and payment are required a minimum of two weeks prior to the start of the class. \n\nJuly 13-17\, 2026 (M-F)\n1:00pm-4:00pm\nDesigning and Writing Questions for Surveys: Guidelines and Recommendations\nPresented by Jennifer (Jen) Dykema\nCourse Fee: $1\,200\n\nThis workshop distills research about survey questions to principles that can be applied to write survey questions that are clear and obtain reliable answers. The workshop provides students with tools to use in diagnosing problems in survey questions and in writing their own survey questions. Sessions combine lectures with group exercises & discussion. The lecture provides guidelines for writing and revising survey questions and illustrates how to revise troubled questions. Sessions consider both questions about events and behaviors and questions about subjective phenomena (such as attitudes\, evaluations\, and internal states).\n\nCOURSE OBJECTIVES\n\nIntroduce a structural analysis of parts of a survey question. Describe guidelines for diagnosing problems in survey questions and writing new survey questions. Focus on the structure and wording of survey questions\, whether for interviewer-administered or self-administered instruments. Provide an opportunity to apply the guidelines and principles during in-class exercises. Focus on improving individual questions and sets of questions. Summarize research that underlies key decisions in writing survey questions. Introduce cognitive interviewing as a method for testing survey questions.\n\nWHO SHOULD ATTEND\n\nIndividuals who will be writing or reviewing survey questions or survey instruments or analyzing survey data. This course gives practical guidance to those who have written survey questions but who are not familiar with the research on question design\, those who are just beginning to design survey instruments\, and those who use survey data but do not themselves design survey instruments.\n\nINSTRUCTOR\n\nJennifer (Jen) Dykema s an Professor of Sociology and the Faculty Director of the University of Wisconsin Survey Center (UWSC). Jen’s research focuses on survey methodology\, identifying sources of errors produced in the process of gathering standardized measurements and developing and implementing methods to reduce those errors. This work examines three main areas of inquiry: questionnaire design\, methods to increase response rates\, and interviewer-respondent interaction. As Faculty Director\, Jen oversees a program of methodological research that incorporates experiments and evaluations in ongoing projects. Her research has appeared in a number of journals including Public Opinion Quarterly\, Journal of Survey Statistics and Methodology\, Social Science Computer Review\, and Field Methods\, and edited volumes including the Handbook of Survey Research and Advances in Questionnaire Design\, Development\, Evaluation and Testing. She recently co-edited “Interviewer Effects from a Total Survey Error Perspective (2020).” Jen served as the Conference Chair for the American Association for Public Opinion Research (AAPOR) in 2017\, and in 2022 she was selected as a Fellow of the Midwest Association for Public Opinion Research (MAPOR). Jen earned her B.A. in psychology and sociology from the University of Michigan\, and her M.S. and Ph.D. in sociology from the University of Wisconsin-Madison. UID:148810-21904778@events.umich.edu URL:https://events.umich.edu/event/148810 CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate and Professional Students,Mathematics,Survey Methodology,Survey Methods,Survey Research LOCATION:Off Campus Location CONTACT: END:VEVENT BEGIN:VEVENT DTSTAMP:20260610T135252 DTSTART;TZID=America/Detroit:20260715T090000 DTEND;TZID=America/Detroit:20260715T160000 SUMMARY:Class / Instruction:Noncredit short courses presented by the Summer Institute in Survey Research Techniques DESCRIPTION:Founded 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\nClasses are open for registration.\nYou do not have to be affiliated with the University to attend. \nRegistration and payment are required a minimum of two weeks prior to the start of the class. \n\nJuly 7 and 9\, 2026 (T/Th)\n9:00am-1:00pm\nInterventions in a Responsive Survey Design Framework\nPresented by Brady T. West\nCourse Fee: $600\n\nJuly 13-17\, 2026 (M-F)\n1:00pm-4:00pm\nDesigning and Writing Questions for Surveys: Guidelines and Recommendations\nPresented by Jennifer (Jen) Dykema\nCourse Fee: $1\,200\n\nJuly 13-17\, 2026 (M-F)\n10:30am-12:00pm\nIntegrating Qualitative Methods into Survey Research\nPresented by Darby Steiger\nCourse Fee: $500\n\nJuly 20-23\, 2026 (M-Th)\n12:00pm-4:00pm\nGoing Deeper into Questionnaire Design with Alternative Methods and Tools\nPresented by Pamela Campanelli\nCourse Fee: $1\,200\n\nJuly 20-30\, 2026 (M T TH: Live instruction\; W: Video instruction)\n10:00am-11:30am\nNatural Language Processing with R\nPresented by Robyn Ferg\nCourse Fee: $1\,200 UID:148807-21904759@events.umich.edu URL:https://events.umich.edu/event/148807 CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Bias,Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate and Professional Students,Lecture,Mathematics,Research,Social Science,Social Sciences,Statistics,Survey Methodology,Survey Methods,Survey Research LOCATION:Off Campus Location CONTACT: END:VEVENT BEGIN:VEVENT DTSTAMP:20260610T143232 DTSTART;TZID=America/Detroit:20260715T103000 DTEND;TZID=America/Detroit:20260715T120000 SUMMARY:Class / Instruction:Integrating Qualitative Methods into Survey Research DESCRIPTION:Founded 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\nClasses are open for registration.\nYou do not have to be affiliated with the University to attend. \nRegistration and payment are required a minimum of two weeks prior to the start of the class. \n\nJuly 13-17\, 2026 (M-F)\n10:30am-12:00pm\nIntegrating Qualitative Methods into Survey Research\nPresented by Darby Steiger\nCourse Fee: $500\n\nThis intensive course is designed to introduce novice and intermediate survey researchers to the integration of qualitative methods into survey research. Guided by the literature on mixed methods research\, the course will present various motivations and strategies for blending qualitative components into a quantitative study. Students will be introduced to a variety of qualitative methods and the ways each approach can complement a survey\, including focus groups\, in-depth interviews\, asynchronous research\, cognitive testing\, open-ended survey questions\, and multiple methods used across a single study. Through case studies and collaborative exercises\, students will explore the potential contribution of each method\, as well as the benefits of combined methods to advance and understand specific research questions. Practical considerations will be covered\, including study design\, sampling\, recruitment\, data collection\, analysis\, and integration of qualitative findings into survey reporting. This course is designed for those with a specific research question in mind\, as participants will be asked to design multi-method approaches to a research question of their choice. By the end of this course\, participants will understand the role qualitative research can play in survey research and how to design and implement a qualitative phase in a multimethod study.\n\nDarby Steiger is Vice President of Innovation & Solutions and Director of Qualitative Research at SSRS. Darby is responsible for spearheading the advancement of the core SSRS research products while driving cutting-edge approaches to the firm’s qualitative and quantitative research divisions. With over 30 years as a qualitative researcher and survey methodologist\, Darby has extensive experience conducting qualitative and quantitative research for a wide range of organizations and topics. A national leader in research methods\, Darby regularly presents at leading industry conferences and recently served on the Executive Council of the American Association for Public Opinion Research. Darby has three degrees from the University of Michigan. UID:148811-21904784@events.umich.edu URL:https://events.umich.edu/event/148811 CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate and Professional Students,Mathematics,Online,Research,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:20260610T141904 DTSTART;TZID=America/Detroit:20260715T130000 DTEND;TZID=America/Detroit:20260715T160000 SUMMARY:Class / Instruction:Designing and Writing Questions for Surveys: Guidelines and Recommendations DESCRIPTION:Founded 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\nClasses are open for registration.\nYou do not have to be affiliated with the University to attend. \nRegistration and payment are required a minimum of two weeks prior to the start of the class. \n\nJuly 13-17\, 2026 (M-F)\n1:00pm-4:00pm\nDesigning and Writing Questions for Surveys: Guidelines and Recommendations\nPresented by Jennifer (Jen) Dykema\nCourse Fee: $1\,200\n\nThis workshop distills research about survey questions to principles that can be applied to write survey questions that are clear and obtain reliable answers. The workshop provides students with tools to use in diagnosing problems in survey questions and in writing their own survey questions. Sessions combine lectures with group exercises & discussion. The lecture provides guidelines for writing and revising survey questions and illustrates how to revise troubled questions. Sessions consider both questions about events and behaviors and questions about subjective phenomena (such as attitudes\, evaluations\, and internal states).\n\nCOURSE OBJECTIVES\n\nIntroduce a structural analysis of parts of a survey question. Describe guidelines for diagnosing problems in survey questions and writing new survey questions. Focus on the structure and wording of survey questions\, whether for interviewer-administered or self-administered instruments. Provide an opportunity to apply the guidelines and principles during in-class exercises. Focus on improving individual questions and sets of questions. Summarize research that underlies key decisions in writing survey questions. Introduce cognitive interviewing as a method for testing survey questions.\n\nWHO SHOULD ATTEND\n\nIndividuals who will be writing or reviewing survey questions or survey instruments or analyzing survey data. This course gives practical guidance to those who have written survey questions but who are not familiar with the research on question design\, those who are just beginning to design survey instruments\, and those who use survey data but do not themselves design survey instruments.\n\nINSTRUCTOR\n\nJennifer (Jen) Dykema s an Professor of Sociology and the Faculty Director of the University of Wisconsin Survey Center (UWSC). Jen’s research focuses on survey methodology\, identifying sources of errors produced in the process of gathering standardized measurements and developing and implementing methods to reduce those errors. This work examines three main areas of inquiry: questionnaire design\, methods to increase response rates\, and interviewer-respondent interaction. As Faculty Director\, Jen oversees a program of methodological research that incorporates experiments and evaluations in ongoing projects. Her research has appeared in a number of journals including Public Opinion Quarterly\, Journal of Survey Statistics and Methodology\, Social Science Computer Review\, and Field Methods\, and edited volumes including the Handbook of Survey Research and Advances in Questionnaire Design\, Development\, Evaluation and Testing. She recently co-edited “Interviewer Effects from a Total Survey Error Perspective (2020).” Jen served as the Conference Chair for the American Association for Public Opinion Research (AAPOR) in 2017\, and in 2022 she was selected as a Fellow of the Midwest Association for Public Opinion Research (MAPOR). Jen earned her B.A. in psychology and sociology from the University of Michigan\, and her M.S. and Ph.D. in sociology from the University of Wisconsin-Madison. UID:148810-21904779@events.umich.edu URL:https://events.umich.edu/event/148810 CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate and Professional Students,Mathematics,Survey Methodology,Survey Methods,Survey Research LOCATION:Off Campus Location CONTACT: END:VEVENT BEGIN:VEVENT DTSTAMP:20260610T135252 DTSTART;TZID=America/Detroit:20260716T090000 DTEND;TZID=America/Detroit:20260716T160000 SUMMARY:Class / Instruction:Noncredit short courses presented by the Summer Institute in Survey Research Techniques DESCRIPTION:Founded 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\nClasses are open for registration.\nYou do not have to be affiliated with the University to attend. \nRegistration and payment are required a minimum of two weeks prior to the start of the class. \n\nJuly 7 and 9\, 2026 (T/Th)\n9:00am-1:00pm\nInterventions in a Responsive Survey Design Framework\nPresented by Brady T. West\nCourse Fee: $600\n\nJuly 13-17\, 2026 (M-F)\n1:00pm-4:00pm\nDesigning and Writing Questions for Surveys: Guidelines and Recommendations\nPresented by Jennifer (Jen) Dykema\nCourse Fee: $1\,200\n\nJuly 13-17\, 2026 (M-F)\n10:30am-12:00pm\nIntegrating Qualitative Methods into Survey Research\nPresented by Darby Steiger\nCourse Fee: $500\n\nJuly 20-23\, 2026 (M-Th)\n12:00pm-4:00pm\nGoing Deeper into Questionnaire Design with Alternative Methods and Tools\nPresented by Pamela Campanelli\nCourse Fee: $1\,200\n\nJuly 20-30\, 2026 (M T TH: Live instruction\; W: Video instruction)\n10:00am-11:30am\nNatural Language Processing with R\nPresented by Robyn Ferg\nCourse Fee: $1\,200 UID:148807-21904760@events.umich.edu URL:https://events.umich.edu/event/148807 CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Bias,Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate and Professional Students,Lecture,Mathematics,Research,Social Science,Social Sciences,Statistics,Survey Methodology,Survey Methods,Survey Research LOCATION:Off Campus Location CONTACT: END:VEVENT BEGIN:VEVENT DTSTAMP:20260610T143232 DTSTART;TZID=America/Detroit:20260716T103000 DTEND;TZID=America/Detroit:20260716T120000 SUMMARY:Class / Instruction:Integrating Qualitative Methods into Survey Research DESCRIPTION:Founded 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\nClasses are open for registration.\nYou do not have to be affiliated with the University to attend. \nRegistration and payment are required a minimum of two weeks prior to the start of the class. \n\nJuly 13-17\, 2026 (M-F)\n10:30am-12:00pm\nIntegrating Qualitative Methods into Survey Research\nPresented by Darby Steiger\nCourse Fee: $500\n\nThis intensive course is designed to introduce novice and intermediate survey researchers to the integration of qualitative methods into survey research. Guided by the literature on mixed methods research\, the course will present various motivations and strategies for blending qualitative components into a quantitative study. Students will be introduced to a variety of qualitative methods and the ways each approach can complement a survey\, including focus groups\, in-depth interviews\, asynchronous research\, cognitive testing\, open-ended survey questions\, and multiple methods used across a single study. Through case studies and collaborative exercises\, students will explore the potential contribution of each method\, as well as the benefits of combined methods to advance and understand specific research questions. Practical considerations will be covered\, including study design\, sampling\, recruitment\, data collection\, analysis\, and integration of qualitative findings into survey reporting. This course is designed for those with a specific research question in mind\, as participants will be asked to design multi-method approaches to a research question of their choice. By the end of this course\, participants will understand the role qualitative research can play in survey research and how to design and implement a qualitative phase in a multimethod study.\n\nDarby Steiger is Vice President of Innovation & Solutions and Director of Qualitative Research at SSRS. Darby is responsible for spearheading the advancement of the core SSRS research products while driving cutting-edge approaches to the firm’s qualitative and quantitative research divisions. With over 30 years as a qualitative researcher and survey methodologist\, Darby has extensive experience conducting qualitative and quantitative research for a wide range of organizations and topics. A national leader in research methods\, Darby regularly presents at leading industry conferences and recently served on the Executive Council of the American Association for Public Opinion Research. Darby has three degrees from the University of Michigan. UID:148811-21904785@events.umich.edu URL:https://events.umich.edu/event/148811 CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate and Professional Students,Mathematics,Online,Research,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:20260610T141904 DTSTART;TZID=America/Detroit:20260716T130000 DTEND;TZID=America/Detroit:20260716T160000 SUMMARY:Class / Instruction:Designing and Writing Questions for Surveys: Guidelines and Recommendations DESCRIPTION:Founded 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\nClasses are open for registration.\nYou do not have to be affiliated with the University to attend. \nRegistration and payment are required a minimum of two weeks prior to the start of the class. \n\nJuly 13-17\, 2026 (M-F)\n1:00pm-4:00pm\nDesigning and Writing Questions for Surveys: Guidelines and Recommendations\nPresented by Jennifer (Jen) Dykema\nCourse Fee: $1\,200\n\nThis workshop distills research about survey questions to principles that can be applied to write survey questions that are clear and obtain reliable answers. The workshop provides students with tools to use in diagnosing problems in survey questions and in writing their own survey questions. Sessions combine lectures with group exercises & discussion. The lecture provides guidelines for writing and revising survey questions and illustrates how to revise troubled questions. Sessions consider both questions about events and behaviors and questions about subjective phenomena (such as attitudes\, evaluations\, and internal states).\n\nCOURSE OBJECTIVES\n\nIntroduce a structural analysis of parts of a survey question. Describe guidelines for diagnosing problems in survey questions and writing new survey questions. Focus on the structure and wording of survey questions\, whether for interviewer-administered or self-administered instruments. Provide an opportunity to apply the guidelines and principles during in-class exercises. Focus on improving individual questions and sets of questions. Summarize research that underlies key decisions in writing survey questions. Introduce cognitive interviewing as a method for testing survey questions.\n\nWHO SHOULD ATTEND\n\nIndividuals who will be writing or reviewing survey questions or survey instruments or analyzing survey data. This course gives practical guidance to those who have written survey questions but who are not familiar with the research on question design\, those who are just beginning to design survey instruments\, and those who use survey data but do not themselves design survey instruments.\n\nINSTRUCTOR\n\nJennifer (Jen) Dykema s an Professor of Sociology and the Faculty Director of the University of Wisconsin Survey Center (UWSC). Jen’s research focuses on survey methodology\, identifying sources of errors produced in the process of gathering standardized measurements and developing and implementing methods to reduce those errors. This work examines three main areas of inquiry: questionnaire design\, methods to increase response rates\, and interviewer-respondent interaction. As Faculty Director\, Jen oversees a program of methodological research that incorporates experiments and evaluations in ongoing projects. Her research has appeared in a number of journals including Public Opinion Quarterly\, Journal of Survey Statistics and Methodology\, Social Science Computer Review\, and Field Methods\, and edited volumes including the Handbook of Survey Research and Advances in Questionnaire Design\, Development\, Evaluation and Testing. She recently co-edited “Interviewer Effects from a Total Survey Error Perspective (2020).” Jen served as the Conference Chair for the American Association for Public Opinion Research (AAPOR) in 2017\, and in 2022 she was selected as a Fellow of the Midwest Association for Public Opinion Research (MAPOR). Jen earned her B.A. in psychology and sociology from the University of Michigan\, and her M.S. and Ph.D. in sociology from the University of Wisconsin-Madison. UID:148810-21904780@events.umich.edu URL:https://events.umich.edu/event/148810 CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate and Professional Students,Mathematics,Survey Methodology,Survey Methods,Survey Research LOCATION:Off Campus Location CONTACT: END:VEVENT BEGIN:VEVENT DTSTAMP:20260610T135252 DTSTART;TZID=America/Detroit:20260717T090000 DTEND;TZID=America/Detroit:20260717T160000 SUMMARY:Class / Instruction:Noncredit short courses presented by the Summer Institute in Survey Research Techniques DESCRIPTION:Founded 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\nClasses are open for registration.\nYou do not have to be affiliated with the University to attend. \nRegistration and payment are required a minimum of two weeks prior to the start of the class. \n\nJuly 7 and 9\, 2026 (T/Th)\n9:00am-1:00pm\nInterventions in a Responsive Survey Design Framework\nPresented by Brady T. West\nCourse Fee: $600\n\nJuly 13-17\, 2026 (M-F)\n1:00pm-4:00pm\nDesigning and Writing Questions for Surveys: Guidelines and Recommendations\nPresented by Jennifer (Jen) Dykema\nCourse Fee: $1\,200\n\nJuly 13-17\, 2026 (M-F)\n10:30am-12:00pm\nIntegrating Qualitative Methods into Survey Research\nPresented by Darby Steiger\nCourse Fee: $500\n\nJuly 20-23\, 2026 (M-Th)\n12:00pm-4:00pm\nGoing Deeper into Questionnaire Design with Alternative Methods and Tools\nPresented by Pamela Campanelli\nCourse Fee: $1\,200\n\nJuly 20-30\, 2026 (M T TH: Live instruction\; W: Video instruction)\n10:00am-11:30am\nNatural Language Processing with R\nPresented by Robyn Ferg\nCourse Fee: $1\,200 UID:148807-21904761@events.umich.edu URL:https://events.umich.edu/event/148807 CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Bias,Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate and Professional Students,Lecture,Mathematics,Research,Social Science,Social Sciences,Statistics,Survey Methodology,Survey Methods,Survey Research LOCATION:Off Campus Location CONTACT: END:VEVENT BEGIN:VEVENT DTSTAMP:20260610T143232 DTSTART;TZID=America/Detroit:20260717T103000 DTEND;TZID=America/Detroit:20260717T120000 SUMMARY:Class / Instruction:Integrating Qualitative Methods into Survey Research DESCRIPTION:Founded 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\nClasses are open for registration.\nYou do not have to be affiliated with the University to attend. \nRegistration and payment are required a minimum of two weeks prior to the start of the class. \n\nJuly 13-17\, 2026 (M-F)\n10:30am-12:00pm\nIntegrating Qualitative Methods into Survey Research\nPresented by Darby Steiger\nCourse Fee: $500\n\nThis intensive course is designed to introduce novice and intermediate survey researchers to the integration of qualitative methods into survey research. Guided by the literature on mixed methods research\, the course will present various motivations and strategies for blending qualitative components into a quantitative study. Students will be introduced to a variety of qualitative methods and the ways each approach can complement a survey\, including focus groups\, in-depth interviews\, asynchronous research\, cognitive testing\, open-ended survey questions\, and multiple methods used across a single study. Through case studies and collaborative exercises\, students will explore the potential contribution of each method\, as well as the benefits of combined methods to advance and understand specific research questions. Practical considerations will be covered\, including study design\, sampling\, recruitment\, data collection\, analysis\, and integration of qualitative findings into survey reporting. This course is designed for those with a specific research question in mind\, as participants will be asked to design multi-method approaches to a research question of their choice. By the end of this course\, participants will understand the role qualitative research can play in survey research and how to design and implement a qualitative phase in a multimethod study.\n\nDarby Steiger is Vice President of Innovation & Solutions and Director of Qualitative Research at SSRS. Darby is responsible for spearheading the advancement of the core SSRS research products while driving cutting-edge approaches to the firm’s qualitative and quantitative research divisions. With over 30 years as a qualitative researcher and survey methodologist\, Darby has extensive experience conducting qualitative and quantitative research for a wide range of organizations and topics. A national leader in research methods\, Darby regularly presents at leading industry conferences and recently served on the Executive Council of the American Association for Public Opinion Research. Darby has three degrees from the University of Michigan. UID:148811-21904786@events.umich.edu URL:https://events.umich.edu/event/148811 CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate and Professional Students,Mathematics,Online,Research,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:20260610T141904 DTSTART;TZID=America/Detroit:20260717T130000 DTEND;TZID=America/Detroit:20260717T160000 SUMMARY:Class / Instruction:Designing and Writing Questions for Surveys: Guidelines and Recommendations DESCRIPTION:Founded 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\nClasses are open for registration.\nYou do not have to be affiliated with the University to attend. \nRegistration and payment are required a minimum of two weeks prior to the start of the class. \n\nJuly 13-17\, 2026 (M-F)\n1:00pm-4:00pm\nDesigning and Writing Questions for Surveys: Guidelines and Recommendations\nPresented by Jennifer (Jen) Dykema\nCourse Fee: $1\,200\n\nThis workshop distills research about survey questions to principles that can be applied to write survey questions that are clear and obtain reliable answers. The workshop provides students with tools to use in diagnosing problems in survey questions and in writing their own survey questions. Sessions combine lectures with group exercises & discussion. The lecture provides guidelines for writing and revising survey questions and illustrates how to revise troubled questions. Sessions consider both questions about events and behaviors and questions about subjective phenomena (such as attitudes\, evaluations\, and internal states).\n\nCOURSE OBJECTIVES\n\nIntroduce a structural analysis of parts of a survey question. Describe guidelines for diagnosing problems in survey questions and writing new survey questions. Focus on the structure and wording of survey questions\, whether for interviewer-administered or self-administered instruments. Provide an opportunity to apply the guidelines and principles during in-class exercises. Focus on improving individual questions and sets of questions. Summarize research that underlies key decisions in writing survey questions. Introduce cognitive interviewing as a method for testing survey questions.\n\nWHO SHOULD ATTEND\n\nIndividuals who will be writing or reviewing survey questions or survey instruments or analyzing survey data. This course gives practical guidance to those who have written survey questions but who are not familiar with the research on question design\, those who are just beginning to design survey instruments\, and those who use survey data but do not themselves design survey instruments.\n\nINSTRUCTOR\n\nJennifer (Jen) Dykema s an Professor of Sociology and the Faculty Director of the University of Wisconsin Survey Center (UWSC). Jen’s research focuses on survey methodology\, identifying sources of errors produced in the process of gathering standardized measurements and developing and implementing methods to reduce those errors. This work examines three main areas of inquiry: questionnaire design\, methods to increase response rates\, and interviewer-respondent interaction. As Faculty Director\, Jen oversees a program of methodological research that incorporates experiments and evaluations in ongoing projects. Her research has appeared in a number of journals including Public Opinion Quarterly\, Journal of Survey Statistics and Methodology\, Social Science Computer Review\, and Field Methods\, and edited volumes including the Handbook of Survey Research and Advances in Questionnaire Design\, Development\, Evaluation and Testing. She recently co-edited “Interviewer Effects from a Total Survey Error Perspective (2020).” Jen served as the Conference Chair for the American Association for Public Opinion Research (AAPOR) in 2017\, and in 2022 she was selected as a Fellow of the Midwest Association for Public Opinion Research (MAPOR). Jen earned her B.A. in psychology and sociology from the University of Michigan\, and her M.S. and Ph.D. in sociology from the University of Wisconsin-Madison. UID:148810-21904781@events.umich.edu URL:https://events.umich.edu/event/148810 CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate and Professional Students,Mathematics,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:20260610T135252 DTSTART;TZID=America/Detroit:20260720T090000 DTEND;TZID=America/Detroit:20260720T160000 SUMMARY:Class / Instruction:Noncredit short courses presented by the Summer Institute in Survey Research Techniques DESCRIPTION:Founded 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\nClasses are open for registration.\nYou do not have to be affiliated with the University to attend. \nRegistration and payment are required a minimum of two weeks prior to the start of the class. \n\nJuly 7 and 9\, 2026 (T/Th)\n9:00am-1:00pm\nInterventions in a Responsive Survey Design Framework\nPresented by Brady T. West\nCourse Fee: $600\n\nJuly 13-17\, 2026 (M-F)\n1:00pm-4:00pm\nDesigning and Writing Questions for Surveys: Guidelines and Recommendations\nPresented by Jennifer (Jen) Dykema\nCourse Fee: $1\,200\n\nJuly 13-17\, 2026 (M-F)\n10:30am-12:00pm\nIntegrating Qualitative Methods into Survey Research\nPresented by Darby Steiger\nCourse Fee: $500\n\nJuly 20-23\, 2026 (M-Th)\n12:00pm-4:00pm\nGoing Deeper into Questionnaire Design with Alternative Methods and Tools\nPresented by Pamela Campanelli\nCourse Fee: $1\,200\n\nJuly 20-30\, 2026 (M T TH: Live instruction\; W: Video instruction)\n10:00am-11:30am\nNatural Language Processing with R\nPresented by Robyn Ferg\nCourse Fee: $1\,200 UID:148807-21904764@events.umich.edu URL:https://events.umich.edu/event/148807 CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Bias,Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate and Professional Students,Lecture,Mathematics,Research,Social Science,Social Sciences,Statistics,Survey Methodology,Survey Methods,Survey Research LOCATION:Off Campus Location CONTACT: END:VEVENT BEGIN:VEVENT DTSTAMP:20260610T151354 DTSTART;TZID=America/Detroit:20260720T100000 DTEND;TZID=America/Detroit:20260720T233000 SUMMARY:Class / Instruction:Natural Language Processing with R DESCRIPTION:Founded 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\nClasses are open for registration.\nYou do not have to be affiliated with the University to attend. \nRegistration and payment are required a minimum of two weeks prior to the start of the class. \n\nJuly 20-30\, 2026 (M T TH: Live instruction\; W: Video instruction)\n10:00am-11:30am\nNatural Language Processing with R\nPresented by Robyn Ferg\nCourse Fee: $1\,200\n\nIn this two-week course\, students will learn a variety of natural language processing methods for analyzing and extracting meaning from text data. The course will start with an introduction to text data\, including text preprocessing and exploratory methods. The topics that follow will include machine learning models used for topic modeling\, clustering\, classification\, sentiment analysis\, and word embeddings. Students will also be introduced to web scraping. Considerations to both long and short texts of various subject matter. Class examples will be demonstrated primarily in R. This course assumes a bachelors-level background in Statistics or related field and knowledge of R or Python\; no prior knowledge of text analysis is assumed.\n\nRobyn Ferg is a senior statistician at Westat. Her doctoral and postdoctoral research focused on developing methods for extracting insights from social media data. She has taught graduate and short courses at the Joint Program in Survey Methodology (University of Maryland) and given talks on text analysis at the Census Bureau\, University of Maryland\, University of Michigan\, Michigan State University\, and several national and international conferences. She has published original research on this topic in several peer reviewed journals. She has a PhD in Statistics from the University of Michigan. UID:148814-21904793@events.umich.edu URL:https://events.umich.edu/event/148814 CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate and Professional Students,Mathematics,Online,Statistics,Survey Methodology,Survey Methods,Survey Research LOCATION:Off Campus Location CONTACT: END:VEVENT BEGIN:VEVENT DTSTAMP:20260610T150300 DTSTART;TZID=America/Detroit:20260720T120000 DTEND;TZID=America/Detroit:20260720T160000 SUMMARY:Class / Instruction:Going Deeper into Questionnaire Design with Alternative Methods and Tools DESCRIPTION:Founded 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\nClasses are open for registration.\nYou do not have to be affiliated with the University to attend. \nRegistration and payment are required a minimum of two weeks prior to the start of the class. \n\nJuly 20-23\, 2026 (M-Th)\n12:00pm-4:00pm\nGoing Deeper into Questionnaire Design with Alternative Methods and Tools\nPresented by Pamela Campanelli\nCourse Fee: $1\,200\n\nThis course assumes you have some level of experience with questionnaire design. It goes beyond looking at question comprehension purely from a cognitive side. The linguistic side will be explored\, including the use of online tools. Factual questions will be revisited but with the goal of exploring different types of respondent memory problems. Solutions include basic aids to improve memory and alternative methods: decomposition\, calendars\, event history calendars\, internet enabled devices\, wearables\, apps and sensors\, and additional tasks on mobile phones. Also covered are the effects of telescoping and quasi-facts. Subjective questions will be revisited to understand attitude inconsistency and to cover the popular topic of satisfaction and other customer experience metrics. Alternatives methods to attitude measurement will also be examined: factorial surveys and multi-item scales. The course concludes with multi-cultural issues raised by Rincón and a mini appendix on ways to translate survey questions and evaluate the translation.\n\nThe course will be interactive with the goal of making it as close to in-person training as possible. There also will be workshops throughout. Dr. Campanelli is happy to chat with participants about their own questionnaires.\n\nWhy take this course?\n\nYou will get to learn about:\n\nThe deeper issues that affect factual and subjective questions.\nA broader set of resources available to solve these issues (including alternative methods and tools).\n* Please note that AI is not included in the alternative tools that will be explored in this course's curriculum.\n\nPrerequisite: An introductory course in questionnaire design or equivalent experience.\n\nPamela Campanelli is a survey methods specialist\, chartered statistician\, fellow of the academy of social sciences and an international trainer\, researcher and consultant who runs her own business (http://www.thesurveycoach.com/). Her background is in social statistics\, survey methodology\, and psychology with a special interest in the study of survey error and data quality focusing on questionnaire design\, question testing strategies\, interviewing techniques\, sampling and weighting\, survey analysis\, and mixed-mode designs. In addition to providing consultancy\, conducting research\, writing papers\, reviewing for journals\, advising committees\, Dr. Campanelli’s focuses on providing training courses. She is committed to high quality learning. She believes in delivering courses that are lively and engaging\, foster an informal and interactive atmosphere\, communicate concepts in a straightforward and accessible way\, illustrate the material through the use of ‘real life’ examples\, and provide workshops to put theory into practice. UID:148812-21904788@events.umich.edu URL:https://events.umich.edu/event/148812 CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate and Professional Students,Mathematics,Online,Research,Science,Social Sciences,Statistics,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:20260610T135252 DTSTART;TZID=America/Detroit:20260721T090000 DTEND;TZID=America/Detroit:20260721T160000 SUMMARY:Class / Instruction:Noncredit short courses presented by the Summer Institute in Survey Research Techniques DESCRIPTION:Founded 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\nClasses are open for registration.\nYou do not have to be affiliated with the University to attend. \nRegistration and payment are required a minimum of two weeks prior to the start of the class. \n\nJuly 7 and 9\, 2026 (T/Th)\n9:00am-1:00pm\nInterventions in a Responsive Survey Design Framework\nPresented by Brady T. West\nCourse Fee: $600\n\nJuly 13-17\, 2026 (M-F)\n1:00pm-4:00pm\nDesigning and Writing Questions for Surveys: Guidelines and Recommendations\nPresented by Jennifer (Jen) Dykema\nCourse Fee: $1\,200\n\nJuly 13-17\, 2026 (M-F)\n10:30am-12:00pm\nIntegrating Qualitative Methods into Survey Research\nPresented by Darby Steiger\nCourse Fee: $500\n\nJuly 20-23\, 2026 (M-Th)\n12:00pm-4:00pm\nGoing Deeper into Questionnaire Design with Alternative Methods and Tools\nPresented by Pamela Campanelli\nCourse Fee: $1\,200\n\nJuly 20-30\, 2026 (M T TH: Live instruction\; W: Video instruction)\n10:00am-11:30am\nNatural Language Processing with R\nPresented by Robyn Ferg\nCourse Fee: $1\,200 UID:148807-21904765@events.umich.edu URL:https://events.umich.edu/event/148807 CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Bias,Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate and Professional Students,Lecture,Mathematics,Research,Social Science,Social Sciences,Statistics,Survey Methodology,Survey Methods,Survey Research LOCATION:Off Campus Location CONTACT: END:VEVENT BEGIN:VEVENT DTSTAMP:20260610T151354 DTSTART;TZID=America/Detroit:20260721T100000 DTEND;TZID=America/Detroit:20260721T233000 SUMMARY:Class / Instruction:Natural Language Processing with R DESCRIPTION:Founded 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\nClasses are open for registration.\nYou do not have to be affiliated with the University to attend. \nRegistration and payment are required a minimum of two weeks prior to the start of the class. \n\nJuly 20-30\, 2026 (M T TH: Live instruction\; W: Video instruction)\n10:00am-11:30am\nNatural Language Processing with R\nPresented by Robyn Ferg\nCourse Fee: $1\,200\n\nIn this two-week course\, students will learn a variety of natural language processing methods for analyzing and extracting meaning from text data. The course will start with an introduction to text data\, including text preprocessing and exploratory methods. The topics that follow will include machine learning models used for topic modeling\, clustering\, classification\, sentiment analysis\, and word embeddings. Students will also be introduced to web scraping. Considerations to both long and short texts of various subject matter. Class examples will be demonstrated primarily in R. This course assumes a bachelors-level background in Statistics or related field and knowledge of R or Python\; no prior knowledge of text analysis is assumed.\n\nRobyn Ferg is a senior statistician at Westat. Her doctoral and postdoctoral research focused on developing methods for extracting insights from social media data. She has taught graduate and short courses at the Joint Program in Survey Methodology (University of Maryland) and given talks on text analysis at the Census Bureau\, University of Maryland\, University of Michigan\, Michigan State University\, and several national and international conferences. She has published original research on this topic in several peer reviewed journals. She has a PhD in Statistics from the University of Michigan. UID:148814-21904794@events.umich.edu URL:https://events.umich.edu/event/148814 CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate and Professional Students,Mathematics,Online,Statistics,Survey Methodology,Survey Methods,Survey Research LOCATION:Off Campus Location CONTACT: END:VEVENT BEGIN:VEVENT DTSTAMP:20260610T150300 DTSTART;TZID=America/Detroit:20260721T120000 DTEND;TZID=America/Detroit:20260721T160000 SUMMARY:Class / Instruction:Going Deeper into Questionnaire Design with Alternative Methods and Tools DESCRIPTION:Founded 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\nClasses are open for registration.\nYou do not have to be affiliated with the University to attend. \nRegistration and payment are required a minimum of two weeks prior to the start of the class. \n\nJuly 20-23\, 2026 (M-Th)\n12:00pm-4:00pm\nGoing Deeper into Questionnaire Design with Alternative Methods and Tools\nPresented by Pamela Campanelli\nCourse Fee: $1\,200\n\nThis course assumes you have some level of experience with questionnaire design. It goes beyond looking at question comprehension purely from a cognitive side. The linguistic side will be explored\, including the use of online tools. Factual questions will be revisited but with the goal of exploring different types of respondent memory problems. Solutions include basic aids to improve memory and alternative methods: decomposition\, calendars\, event history calendars\, internet enabled devices\, wearables\, apps and sensors\, and additional tasks on mobile phones. Also covered are the effects of telescoping and quasi-facts. Subjective questions will be revisited to understand attitude inconsistency and to cover the popular topic of satisfaction and other customer experience metrics. Alternatives methods to attitude measurement will also be examined: factorial surveys and multi-item scales. The course concludes with multi-cultural issues raised by Rincón and a mini appendix on ways to translate survey questions and evaluate the translation.\n\nThe course will be interactive with the goal of making it as close to in-person training as possible. There also will be workshops throughout. Dr. Campanelli is happy to chat with participants about their own questionnaires.\n\nWhy take this course?\n\nYou will get to learn about:\n\nThe deeper issues that affect factual and subjective questions.\nA broader set of resources available to solve these issues (including alternative methods and tools).\n* Please note that AI is not included in the alternative tools that will be explored in this course's curriculum.\n\nPrerequisite: An introductory course in questionnaire design or equivalent experience.\n\nPamela Campanelli is a survey methods specialist\, chartered statistician\, fellow of the academy of social sciences and an international trainer\, researcher and consultant who runs her own business (http://www.thesurveycoach.com/). Her background is in social statistics\, survey methodology\, and psychology with a special interest in the study of survey error and data quality focusing on questionnaire design\, question testing strategies\, interviewing techniques\, sampling and weighting\, survey analysis\, and mixed-mode designs. In addition to providing consultancy\, conducting research\, writing papers\, reviewing for journals\, advising committees\, Dr. Campanelli’s focuses on providing training courses. She is committed to high quality learning. She believes in delivering courses that are lively and engaging\, foster an informal and interactive atmosphere\, communicate concepts in a straightforward and accessible way\, illustrate the material through the use of ‘real life’ examples\, and provide workshops to put theory into practice. UID:148812-21904789@events.umich.edu URL:https://events.umich.edu/event/148812 CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate and Professional Students,Mathematics,Online,Research,Science,Social Sciences,Statistics,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:20260610T135252 DTSTART;TZID=America/Detroit:20260722T090000 DTEND;TZID=America/Detroit:20260722T160000 SUMMARY:Class / Instruction:Noncredit short courses presented by the Summer Institute in Survey Research Techniques DESCRIPTION:Founded 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\nClasses are open for registration.\nYou do not have to be affiliated with the University to attend. \nRegistration and payment are required a minimum of two weeks prior to the start of the class. \n\nJuly 7 and 9\, 2026 (T/Th)\n9:00am-1:00pm\nInterventions in a Responsive Survey Design Framework\nPresented by Brady T. West\nCourse Fee: $600\n\nJuly 13-17\, 2026 (M-F)\n1:00pm-4:00pm\nDesigning and Writing Questions for Surveys: Guidelines and Recommendations\nPresented by Jennifer (Jen) Dykema\nCourse Fee: $1\,200\n\nJuly 13-17\, 2026 (M-F)\n10:30am-12:00pm\nIntegrating Qualitative Methods into Survey Research\nPresented by Darby Steiger\nCourse Fee: $500\n\nJuly 20-23\, 2026 (M-Th)\n12:00pm-4:00pm\nGoing Deeper into Questionnaire Design with Alternative Methods and Tools\nPresented by Pamela Campanelli\nCourse Fee: $1\,200\n\nJuly 20-30\, 2026 (M T TH: Live instruction\; W: Video instruction)\n10:00am-11:30am\nNatural Language Processing with R\nPresented by Robyn Ferg\nCourse Fee: $1\,200 UID:148807-21904766@events.umich.edu URL:https://events.umich.edu/event/148807 CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Bias,Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate and Professional Students,Lecture,Mathematics,Research,Social Science,Social Sciences,Statistics,Survey Methodology,Survey Methods,Survey Research LOCATION:Off Campus Location CONTACT: END:VEVENT BEGIN:VEVENT DTSTAMP:20260610T151354 DTSTART;TZID=America/Detroit:20260722T100000 DTEND;TZID=America/Detroit:20260722T233000 SUMMARY:Class / Instruction:Natural Language Processing with R DESCRIPTION:Founded 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\nClasses are open for registration.\nYou do not have to be affiliated with the University to attend. \nRegistration and payment are required a minimum of two weeks prior to the start of the class. \n\nJuly 20-30\, 2026 (M T TH: Live instruction\; W: Video instruction)\n10:00am-11:30am\nNatural Language Processing with R\nPresented by Robyn Ferg\nCourse Fee: $1\,200\n\nIn this two-week course\, students will learn a variety of natural language processing methods for analyzing and extracting meaning from text data. The course will start with an introduction to text data\, including text preprocessing and exploratory methods. The topics that follow will include machine learning models used for topic modeling\, clustering\, classification\, sentiment analysis\, and word embeddings. Students will also be introduced to web scraping. Considerations to both long and short texts of various subject matter. Class examples will be demonstrated primarily in R. This course assumes a bachelors-level background in Statistics or related field and knowledge of R or Python\; no prior knowledge of text analysis is assumed.\n\nRobyn Ferg is a senior statistician at Westat. Her doctoral and postdoctoral research focused on developing methods for extracting insights from social media data. She has taught graduate and short courses at the Joint Program in Survey Methodology (University of Maryland) and given talks on text analysis at the Census Bureau\, University of Maryland\, University of Michigan\, Michigan State University\, and several national and international conferences. She has published original research on this topic in several peer reviewed journals. She has a PhD in Statistics from the University of Michigan. UID:148814-21904795@events.umich.edu URL:https://events.umich.edu/event/148814 CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate and Professional Students,Mathematics,Online,Statistics,Survey Methodology,Survey Methods,Survey Research LOCATION:Off Campus Location CONTACT: END:VEVENT BEGIN:VEVENT DTSTAMP:20260610T150300 DTSTART;TZID=America/Detroit:20260722T120000 DTEND;TZID=America/Detroit:20260722T160000 SUMMARY:Class / Instruction:Going Deeper into Questionnaire Design with Alternative Methods and Tools DESCRIPTION:Founded 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\nClasses are open for registration.\nYou do not have to be affiliated with the University to attend. \nRegistration and payment are required a minimum of two weeks prior to the start of the class. \n\nJuly 20-23\, 2026 (M-Th)\n12:00pm-4:00pm\nGoing Deeper into Questionnaire Design with Alternative Methods and Tools\nPresented by Pamela Campanelli\nCourse Fee: $1\,200\n\nThis course assumes you have some level of experience with questionnaire design. It goes beyond looking at question comprehension purely from a cognitive side. The linguistic side will be explored\, including the use of online tools. Factual questions will be revisited but with the goal of exploring different types of respondent memory problems. Solutions include basic aids to improve memory and alternative methods: decomposition\, calendars\, event history calendars\, internet enabled devices\, wearables\, apps and sensors\, and additional tasks on mobile phones. Also covered are the effects of telescoping and quasi-facts. Subjective questions will be revisited to understand attitude inconsistency and to cover the popular topic of satisfaction and other customer experience metrics. Alternatives methods to attitude measurement will also be examined: factorial surveys and multi-item scales. The course concludes with multi-cultural issues raised by Rincón and a mini appendix on ways to translate survey questions and evaluate the translation.\n\nThe course will be interactive with the goal of making it as close to in-person training as possible. There also will be workshops throughout. Dr. Campanelli is happy to chat with participants about their own questionnaires.\n\nWhy take this course?\n\nYou will get to learn about:\n\nThe deeper issues that affect factual and subjective questions.\nA broader set of resources available to solve these issues (including alternative methods and tools).\n* Please note that AI is not included in the alternative tools that will be explored in this course's curriculum.\n\nPrerequisite: An introductory course in questionnaire design or equivalent experience.\n\nPamela Campanelli is a survey methods specialist\, chartered statistician\, fellow of the academy of social sciences and an international trainer\, researcher and consultant who runs her own business (http://www.thesurveycoach.com/). Her background is in social statistics\, survey methodology\, and psychology with a special interest in the study of survey error and data quality focusing on questionnaire design\, question testing strategies\, interviewing techniques\, sampling and weighting\, survey analysis\, and mixed-mode designs. In addition to providing consultancy\, conducting research\, writing papers\, reviewing for journals\, advising committees\, Dr. Campanelli’s focuses on providing training courses. She is committed to high quality learning. She believes in delivering courses that are lively and engaging\, foster an informal and interactive atmosphere\, communicate concepts in a straightforward and accessible way\, illustrate the material through the use of ‘real life’ examples\, and provide workshops to put theory into practice. UID:148812-21904790@events.umich.edu URL:https://events.umich.edu/event/148812 CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate and Professional Students,Mathematics,Online,Research,Science,Social Sciences,Statistics,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:20260610T135252 DTSTART;TZID=America/Detroit:20260723T090000 DTEND;TZID=America/Detroit:20260723T160000 SUMMARY:Class / Instruction:Noncredit short courses presented by the Summer Institute in Survey Research Techniques DESCRIPTION:Founded 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\nClasses are open for registration.\nYou do not have to be affiliated with the University to attend. \nRegistration and payment are required a minimum of two weeks prior to the start of the class. \n\nJuly 7 and 9\, 2026 (T/Th)\n9:00am-1:00pm\nInterventions in a Responsive Survey Design Framework\nPresented by Brady T. West\nCourse Fee: $600\n\nJuly 13-17\, 2026 (M-F)\n1:00pm-4:00pm\nDesigning and Writing Questions for Surveys: Guidelines and Recommendations\nPresented by Jennifer (Jen) Dykema\nCourse Fee: $1\,200\n\nJuly 13-17\, 2026 (M-F)\n10:30am-12:00pm\nIntegrating Qualitative Methods into Survey Research\nPresented by Darby Steiger\nCourse Fee: $500\n\nJuly 20-23\, 2026 (M-Th)\n12:00pm-4:00pm\nGoing Deeper into Questionnaire Design with Alternative Methods and Tools\nPresented by Pamela Campanelli\nCourse Fee: $1\,200\n\nJuly 20-30\, 2026 (M T TH: Live instruction\; W: Video instruction)\n10:00am-11:30am\nNatural Language Processing with R\nPresented by Robyn Ferg\nCourse Fee: $1\,200 UID:148807-21904767@events.umich.edu URL:https://events.umich.edu/event/148807 CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Bias,Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate and Professional Students,Lecture,Mathematics,Research,Social Science,Social Sciences,Statistics,Survey Methodology,Survey Methods,Survey Research LOCATION:Off Campus Location CONTACT: END:VEVENT BEGIN:VEVENT DTSTAMP:20260610T151354 DTSTART;TZID=America/Detroit:20260723T100000 DTEND;TZID=America/Detroit:20260723T233000 SUMMARY:Class / Instruction:Natural Language Processing with R DESCRIPTION:Founded 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\nClasses are open for registration.\nYou do not have to be affiliated with the University to attend. \nRegistration and payment are required a minimum of two weeks prior to the start of the class. \n\nJuly 20-30\, 2026 (M T TH: Live instruction\; W: Video instruction)\n10:00am-11:30am\nNatural Language Processing with R\nPresented by Robyn Ferg\nCourse Fee: $1\,200\n\nIn this two-week course\, students will learn a variety of natural language processing methods for analyzing and extracting meaning from text data. The course will start with an introduction to text data\, including text preprocessing and exploratory methods. The topics that follow will include machine learning models used for topic modeling\, clustering\, classification\, sentiment analysis\, and word embeddings. Students will also be introduced to web scraping. Considerations to both long and short texts of various subject matter. Class examples will be demonstrated primarily in R. This course assumes a bachelors-level background in Statistics or related field and knowledge of R or Python\; no prior knowledge of text analysis is assumed.\n\nRobyn Ferg is a senior statistician at Westat. Her doctoral and postdoctoral research focused on developing methods for extracting insights from social media data. She has taught graduate and short courses at the Joint Program in Survey Methodology (University of Maryland) and given talks on text analysis at the Census Bureau\, University of Maryland\, University of Michigan\, Michigan State University\, and several national and international conferences. She has published original research on this topic in several peer reviewed journals. She has a PhD in Statistics from the University of Michigan. UID:148814-21904796@events.umich.edu URL:https://events.umich.edu/event/148814 CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate and Professional Students,Mathematics,Online,Statistics,Survey Methodology,Survey Methods,Survey Research LOCATION:Off Campus Location CONTACT: END:VEVENT BEGIN:VEVENT DTSTAMP:20260610T150300 DTSTART;TZID=America/Detroit:20260723T120000 DTEND;TZID=America/Detroit:20260723T160000 SUMMARY:Class / Instruction:Going Deeper into Questionnaire Design with Alternative Methods and Tools DESCRIPTION:Founded 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\nClasses are open for registration.\nYou do not have to be affiliated with the University to attend. \nRegistration and payment are required a minimum of two weeks prior to the start of the class. \n\nJuly 20-23\, 2026 (M-Th)\n12:00pm-4:00pm\nGoing Deeper into Questionnaire Design with Alternative Methods and Tools\nPresented by Pamela Campanelli\nCourse Fee: $1\,200\n\nThis course assumes you have some level of experience with questionnaire design. It goes beyond looking at question comprehension purely from a cognitive side. The linguistic side will be explored\, including the use of online tools. Factual questions will be revisited but with the goal of exploring different types of respondent memory problems. Solutions include basic aids to improve memory and alternative methods: decomposition\, calendars\, event history calendars\, internet enabled devices\, wearables\, apps and sensors\, and additional tasks on mobile phones. Also covered are the effects of telescoping and quasi-facts. Subjective questions will be revisited to understand attitude inconsistency and to cover the popular topic of satisfaction and other customer experience metrics. Alternatives methods to attitude measurement will also be examined: factorial surveys and multi-item scales. The course concludes with multi-cultural issues raised by Rincón and a mini appendix on ways to translate survey questions and evaluate the translation.\n\nThe course will be interactive with the goal of making it as close to in-person training as possible. There also will be workshops throughout. Dr. Campanelli is happy to chat with participants about their own questionnaires.\n\nWhy take this course?\n\nYou will get to learn about:\n\nThe deeper issues that affect factual and subjective questions.\nA broader set of resources available to solve these issues (including alternative methods and tools).\n* Please note that AI is not included in the alternative tools that will be explored in this course's curriculum.\n\nPrerequisite: An introductory course in questionnaire design or equivalent experience.\n\nPamela Campanelli is a survey methods specialist\, chartered statistician\, fellow of the academy of social sciences and an international trainer\, researcher and consultant who runs her own business (http://www.thesurveycoach.com/). Her background is in social statistics\, survey methodology\, and psychology with a special interest in the study of survey error and data quality focusing on questionnaire design\, question testing strategies\, interviewing techniques\, sampling and weighting\, survey analysis\, and mixed-mode designs. In addition to providing consultancy\, conducting research\, writing papers\, reviewing for journals\, advising committees\, Dr. Campanelli’s focuses on providing training courses. She is committed to high quality learning. She believes in delivering courses that are lively and engaging\, foster an informal and interactive atmosphere\, communicate concepts in a straightforward and accessible way\, illustrate the material through the use of ‘real life’ examples\, and provide workshops to put theory into practice. UID:148812-21904791@events.umich.edu URL:https://events.umich.edu/event/148812 CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate and Professional Students,Mathematics,Online,Research,Science,Social Sciences,Statistics,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:20260610T135252 DTSTART;TZID=America/Detroit:20260724T090000 DTEND;TZID=America/Detroit:20260724T160000 SUMMARY:Class / Instruction:Noncredit short courses presented by the Summer Institute in Survey Research Techniques DESCRIPTION:Founded 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\nClasses are open for registration.\nYou do not have to be affiliated with the University to attend. \nRegistration and payment are required a minimum of two weeks prior to the start of the class. \n\nJuly 7 and 9\, 2026 (T/Th)\n9:00am-1:00pm\nInterventions in a Responsive Survey Design Framework\nPresented by Brady T. West\nCourse Fee: $600\n\nJuly 13-17\, 2026 (M-F)\n1:00pm-4:00pm\nDesigning and Writing Questions for Surveys: Guidelines and Recommendations\nPresented by Jennifer (Jen) Dykema\nCourse Fee: $1\,200\n\nJuly 13-17\, 2026 (M-F)\n10:30am-12:00pm\nIntegrating Qualitative Methods into Survey Research\nPresented by Darby Steiger\nCourse Fee: $500\n\nJuly 20-23\, 2026 (M-Th)\n12:00pm-4:00pm\nGoing Deeper into Questionnaire Design with Alternative Methods and Tools\nPresented by Pamela Campanelli\nCourse Fee: $1\,200\n\nJuly 20-30\, 2026 (M T TH: Live instruction\; W: Video instruction)\n10:00am-11:30am\nNatural Language Processing with R\nPresented by Robyn Ferg\nCourse Fee: $1\,200 UID:148807-21904768@events.umich.edu URL:https://events.umich.edu/event/148807 CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Bias,Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate and Professional Students,Lecture,Mathematics,Research,Social Science,Social Sciences,Statistics,Survey Methodology,Survey Methods,Survey Research LOCATION:Off Campus Location CONTACT: END:VEVENT BEGIN:VEVENT DTSTAMP:20260610T151354 DTSTART;TZID=America/Detroit:20260724T100000 DTEND;TZID=America/Detroit:20260724T233000 SUMMARY:Class / Instruction:Natural Language Processing with R DESCRIPTION:Founded 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\nClasses are open for registration.\nYou do not have to be affiliated with the University to attend. \nRegistration and payment are required a minimum of two weeks prior to the start of the class. \n\nJuly 20-30\, 2026 (M T TH: Live instruction\; W: Video instruction)\n10:00am-11:30am\nNatural Language Processing with R\nPresented by Robyn Ferg\nCourse Fee: $1\,200\n\nIn this two-week course\, students will learn a variety of natural language processing methods for analyzing and extracting meaning from text data. The course will start with an introduction to text data\, including text preprocessing and exploratory methods. The topics that follow will include machine learning models used for topic modeling\, clustering\, classification\, sentiment analysis\, and word embeddings. Students will also be introduced to web scraping. Considerations to both long and short texts of various subject matter. Class examples will be demonstrated primarily in R. This course assumes a bachelors-level background in Statistics or related field and knowledge of R or Python\; no prior knowledge of text analysis is assumed.\n\nRobyn Ferg is a senior statistician at Westat. Her doctoral and postdoctoral research focused on developing methods for extracting insights from social media data. She has taught graduate and short courses at the Joint Program in Survey Methodology (University of Maryland) and given talks on text analysis at the Census Bureau\, University of Maryland\, University of Michigan\, Michigan State University\, and several national and international conferences. She has published original research on this topic in several peer reviewed journals. She has a PhD in Statistics from the University of Michigan. UID:148814-21904797@events.umich.edu URL:https://events.umich.edu/event/148814 CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate and Professional Students,Mathematics,Online,Statistics,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:20260610T135252 DTSTART;TZID=America/Detroit:20260727T090000 DTEND;TZID=America/Detroit:20260727T160000 SUMMARY:Class / Instruction:Noncredit short courses presented by the Summer Institute in Survey Research Techniques DESCRIPTION:Founded 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\nClasses are open for registration.\nYou do not have to be affiliated with the University to attend. \nRegistration and payment are required a minimum of two weeks prior to the start of the class. \n\nJuly 7 and 9\, 2026 (T/Th)\n9:00am-1:00pm\nInterventions in a Responsive Survey Design Framework\nPresented by Brady T. West\nCourse Fee: $600\n\nJuly 13-17\, 2026 (M-F)\n1:00pm-4:00pm\nDesigning and Writing Questions for Surveys: Guidelines and Recommendations\nPresented by Jennifer (Jen) Dykema\nCourse Fee: $1\,200\n\nJuly 13-17\, 2026 (M-F)\n10:30am-12:00pm\nIntegrating Qualitative Methods into Survey Research\nPresented by Darby Steiger\nCourse Fee: $500\n\nJuly 20-23\, 2026 (M-Th)\n12:00pm-4:00pm\nGoing Deeper into Questionnaire Design with Alternative Methods and Tools\nPresented by Pamela Campanelli\nCourse Fee: $1\,200\n\nJuly 20-30\, 2026 (M T TH: Live instruction\; W: Video instruction)\n10:00am-11:30am\nNatural Language Processing with R\nPresented by Robyn Ferg\nCourse Fee: $1\,200 UID:148807-21904771@events.umich.edu URL:https://events.umich.edu/event/148807 CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Bias,Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate and Professional Students,Lecture,Mathematics,Research,Social Science,Social Sciences,Statistics,Survey Methodology,Survey Methods,Survey Research LOCATION:Off Campus Location CONTACT: END:VEVENT BEGIN:VEVENT DTSTAMP:20260610T151354 DTSTART;TZID=America/Detroit:20260727T100000 DTEND;TZID=America/Detroit:20260727T233000 SUMMARY:Class / Instruction:Natural Language Processing with R DESCRIPTION:Founded 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\nClasses are open for registration.\nYou do not have to be affiliated with the University to attend. \nRegistration and payment are required a minimum of two weeks prior to the start of the class. \n\nJuly 20-30\, 2026 (M T TH: Live instruction\; W: Video instruction)\n10:00am-11:30am\nNatural Language Processing with R\nPresented by Robyn Ferg\nCourse Fee: $1\,200\n\nIn this two-week course\, students will learn a variety of natural language processing methods for analyzing and extracting meaning from text data. The course will start with an introduction to text data\, including text preprocessing and exploratory methods. The topics that follow will include machine learning models used for topic modeling\, clustering\, classification\, sentiment analysis\, and word embeddings. Students will also be introduced to web scraping. Considerations to both long and short texts of various subject matter. Class examples will be demonstrated primarily in R. This course assumes a bachelors-level background in Statistics or related field and knowledge of R or Python\; no prior knowledge of text analysis is assumed.\n\nRobyn Ferg is a senior statistician at Westat. Her doctoral and postdoctoral research focused on developing methods for extracting insights from social media data. She has taught graduate and short courses at the Joint Program in Survey Methodology (University of Maryland) and given talks on text analysis at the Census Bureau\, University of Maryland\, University of Michigan\, Michigan State University\, and several national and international conferences. She has published original research on this topic in several peer reviewed journals. She has a PhD in Statistics from the University of Michigan. UID:148814-21904800@events.umich.edu URL:https://events.umich.edu/event/148814 CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate and Professional Students,Mathematics,Online,Statistics,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:20260610T135252 DTSTART;TZID=America/Detroit:20260728T090000 DTEND;TZID=America/Detroit:20260728T160000 SUMMARY:Class / Instruction:Noncredit short courses presented by the Summer Institute in Survey Research Techniques DESCRIPTION:Founded 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\nClasses are open for registration.\nYou do not have to be affiliated with the University to attend. \nRegistration and payment are required a minimum of two weeks prior to the start of the class. \n\nJuly 7 and 9\, 2026 (T/Th)\n9:00am-1:00pm\nInterventions in a Responsive Survey Design Framework\nPresented by Brady T. West\nCourse Fee: $600\n\nJuly 13-17\, 2026 (M-F)\n1:00pm-4:00pm\nDesigning and Writing Questions for Surveys: Guidelines and Recommendations\nPresented by Jennifer (Jen) Dykema\nCourse Fee: $1\,200\n\nJuly 13-17\, 2026 (M-F)\n10:30am-12:00pm\nIntegrating Qualitative Methods into Survey Research\nPresented by Darby Steiger\nCourse Fee: $500\n\nJuly 20-23\, 2026 (M-Th)\n12:00pm-4:00pm\nGoing Deeper into Questionnaire Design with Alternative Methods and Tools\nPresented by Pamela Campanelli\nCourse Fee: $1\,200\n\nJuly 20-30\, 2026 (M T TH: Live instruction\; W: Video instruction)\n10:00am-11:30am\nNatural Language Processing with R\nPresented by Robyn Ferg\nCourse Fee: $1\,200 UID:148807-21904772@events.umich.edu URL:https://events.umich.edu/event/148807 CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Bias,Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate and Professional Students,Lecture,Mathematics,Research,Social Science,Social Sciences,Statistics,Survey Methodology,Survey Methods,Survey Research LOCATION:Off Campus Location CONTACT: END:VEVENT BEGIN:VEVENT DTSTAMP:20260610T151354 DTSTART;TZID=America/Detroit:20260728T100000 DTEND;TZID=America/Detroit:20260728T233000 SUMMARY:Class / Instruction:Natural Language Processing with R DESCRIPTION:Founded 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\nClasses are open for registration.\nYou do not have to be affiliated with the University to attend. \nRegistration and payment are required a minimum of two weeks prior to the start of the class. \n\nJuly 20-30\, 2026 (M T TH: Live instruction\; W: Video instruction)\n10:00am-11:30am\nNatural Language Processing with R\nPresented by Robyn Ferg\nCourse Fee: $1\,200\n\nIn this two-week course\, students will learn a variety of natural language processing methods for analyzing and extracting meaning from text data. The course will start with an introduction to text data\, including text preprocessing and exploratory methods. The topics that follow will include machine learning models used for topic modeling\, clustering\, classification\, sentiment analysis\, and word embeddings. Students will also be introduced to web scraping. Considerations to both long and short texts of various subject matter. Class examples will be demonstrated primarily in R. This course assumes a bachelors-level background in Statistics or related field and knowledge of R or Python\; no prior knowledge of text analysis is assumed.\n\nRobyn Ferg is a senior statistician at Westat. Her doctoral and postdoctoral research focused on developing methods for extracting insights from social media data. She has taught graduate and short courses at the Joint Program in Survey Methodology (University of Maryland) and given talks on text analysis at the Census Bureau\, University of Maryland\, University of Michigan\, Michigan State University\, and several national and international conferences. She has published original research on this topic in several peer reviewed journals. She has a PhD in Statistics from the University of Michigan. UID:148814-21904801@events.umich.edu URL:https://events.umich.edu/event/148814 CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate and Professional Students,Mathematics,Online,Statistics,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:20260610T135252 DTSTART;TZID=America/Detroit:20260729T090000 DTEND;TZID=America/Detroit:20260729T160000 SUMMARY:Class / Instruction:Noncredit short courses presented by the Summer Institute in Survey Research Techniques DESCRIPTION:Founded 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\nClasses are open for registration.\nYou do not have to be affiliated with the University to attend. \nRegistration and payment are required a minimum of two weeks prior to the start of the class. \n\nJuly 7 and 9\, 2026 (T/Th)\n9:00am-1:00pm\nInterventions in a Responsive Survey Design Framework\nPresented by Brady T. West\nCourse Fee: $600\n\nJuly 13-17\, 2026 (M-F)\n1:00pm-4:00pm\nDesigning and Writing Questions for Surveys: Guidelines and Recommendations\nPresented by Jennifer (Jen) Dykema\nCourse Fee: $1\,200\n\nJuly 13-17\, 2026 (M-F)\n10:30am-12:00pm\nIntegrating Qualitative Methods into Survey Research\nPresented by Darby Steiger\nCourse Fee: $500\n\nJuly 20-23\, 2026 (M-Th)\n12:00pm-4:00pm\nGoing Deeper into Questionnaire Design with Alternative Methods and Tools\nPresented by Pamela Campanelli\nCourse Fee: $1\,200\n\nJuly 20-30\, 2026 (M T TH: Live instruction\; W: Video instruction)\n10:00am-11:30am\nNatural Language Processing with R\nPresented by Robyn Ferg\nCourse Fee: $1\,200 UID:148807-21904773@events.umich.edu URL:https://events.umich.edu/event/148807 CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Bias,Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate and Professional Students,Lecture,Mathematics,Research,Social Science,Social Sciences,Statistics,Survey Methodology,Survey Methods,Survey Research LOCATION:Off Campus Location CONTACT: END:VEVENT BEGIN:VEVENT DTSTAMP:20260610T151354 DTSTART;TZID=America/Detroit:20260729T100000 DTEND;TZID=America/Detroit:20260729T233000 SUMMARY:Class / Instruction:Natural Language Processing with R DESCRIPTION:Founded 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\nClasses are open for registration.\nYou do not have to be affiliated with the University to attend. \nRegistration and payment are required a minimum of two weeks prior to the start of the class. \n\nJuly 20-30\, 2026 (M T TH: Live instruction\; W: Video instruction)\n10:00am-11:30am\nNatural Language Processing with R\nPresented by Robyn Ferg\nCourse Fee: $1\,200\n\nIn this two-week course\, students will learn a variety of natural language processing methods for analyzing and extracting meaning from text data. The course will start with an introduction to text data\, including text preprocessing and exploratory methods. The topics that follow will include machine learning models used for topic modeling\, clustering\, classification\, sentiment analysis\, and word embeddings. Students will also be introduced to web scraping. Considerations to both long and short texts of various subject matter. Class examples will be demonstrated primarily in R. This course assumes a bachelors-level background in Statistics or related field and knowledge of R or Python\; no prior knowledge of text analysis is assumed.\n\nRobyn Ferg is a senior statistician at Westat. Her doctoral and postdoctoral research focused on developing methods for extracting insights from social media data. She has taught graduate and short courses at the Joint Program in Survey Methodology (University of Maryland) and given talks on text analysis at the Census Bureau\, University of Maryland\, University of Michigan\, Michigan State University\, and several national and international conferences. She has published original research on this topic in several peer reviewed journals. She has a PhD in Statistics from the University of Michigan. UID:148814-21904802@events.umich.edu URL:https://events.umich.edu/event/148814 CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate and Professional Students,Mathematics,Online,Statistics,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:20260610T135252 DTSTART;TZID=America/Detroit:20260730T090000 DTEND;TZID=America/Detroit:20260730T160000 SUMMARY:Class / Instruction:Noncredit short courses presented by the Summer Institute in Survey Research Techniques DESCRIPTION:Founded 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\nClasses are open for registration.\nYou do not have to be affiliated with the University to attend. \nRegistration and payment are required a minimum of two weeks prior to the start of the class. \n\nJuly 7 and 9\, 2026 (T/Th)\n9:00am-1:00pm\nInterventions in a Responsive Survey Design Framework\nPresented by Brady T. West\nCourse Fee: $600\n\nJuly 13-17\, 2026 (M-F)\n1:00pm-4:00pm\nDesigning and Writing Questions for Surveys: Guidelines and Recommendations\nPresented by Jennifer (Jen) Dykema\nCourse Fee: $1\,200\n\nJuly 13-17\, 2026 (M-F)\n10:30am-12:00pm\nIntegrating Qualitative Methods into Survey Research\nPresented by Darby Steiger\nCourse Fee: $500\n\nJuly 20-23\, 2026 (M-Th)\n12:00pm-4:00pm\nGoing Deeper into Questionnaire Design with Alternative Methods and Tools\nPresented by Pamela Campanelli\nCourse Fee: $1\,200\n\nJuly 20-30\, 2026 (M T TH: Live instruction\; W: Video instruction)\n10:00am-11:30am\nNatural Language Processing with R\nPresented by Robyn Ferg\nCourse Fee: $1\,200 UID:148807-21904774@events.umich.edu URL:https://events.umich.edu/event/148807 CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Bias,Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate and Professional Students,Lecture,Mathematics,Research,Social Science,Social Sciences,Statistics,Survey Methodology,Survey Methods,Survey Research LOCATION:Off Campus Location CONTACT: END:VEVENT BEGIN:VEVENT DTSTAMP:20260610T151354 DTSTART;TZID=America/Detroit:20260730T100000 DTEND;TZID=America/Detroit:20260730T233000 SUMMARY:Class / Instruction:Natural Language Processing with R DESCRIPTION:Founded 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\nClasses are open for registration.\nYou do not have to be affiliated with the University to attend. \nRegistration and payment are required a minimum of two weeks prior to the start of the class. \n\nJuly 20-30\, 2026 (M T TH: Live instruction\; W: Video instruction)\n10:00am-11:30am\nNatural Language Processing with R\nPresented by Robyn Ferg\nCourse Fee: $1\,200\n\nIn this two-week course\, students will learn a variety of natural language processing methods for analyzing and extracting meaning from text data. The course will start with an introduction to text data\, including text preprocessing and exploratory methods. The topics that follow will include machine learning models used for topic modeling\, clustering\, classification\, sentiment analysis\, and word embeddings. Students will also be introduced to web scraping. Considerations to both long and short texts of various subject matter. Class examples will be demonstrated primarily in R. This course assumes a bachelors-level background in Statistics or related field and knowledge of R or Python\; no prior knowledge of text analysis is assumed.\n\nRobyn Ferg is a senior statistician at Westat. Her doctoral and postdoctoral research focused on developing methods for extracting insights from social media data. She has taught graduate and short courses at the Joint Program in Survey Methodology (University of Maryland) and given talks on text analysis at the Census Bureau\, University of Maryland\, University of Michigan\, Michigan State University\, and several national and international conferences. She has published original research on this topic in several peer reviewed journals. She has a PhD in Statistics from the University of Michigan. UID:148814-21904803@events.umich.edu URL:https://events.umich.edu/event/148814 CLASS:PUBLIC STATUS:CONFIRMED CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate and Professional Students,Mathematics,Online,Statistics,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