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DTSTAMP:20260513T131053
DTSTART;TZID=America/Detroit:20260604T130000
DTEND;TZID=America/Detroit:20260604T160000
SUMMARY:Class / Instruction:June 1-5 Course - Introduction to Qualitative Research Methods
DESCRIPTION:June 1-5\, 2026\, M-F\n1:00-4:00pm \nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nIntroduction to Qualitative Research Methods\n\nThis introductory course provides students with a strong foundation in qualitative research\, covering principles of qualitative research\, study design including participant recruitment and sample size estimation. Students also learn how to design and conduct core data collection methods - in-depth interviews\, focus groups\, and observation – and a range of field tasks such as transcription and field training. Then writing and critiquing qualitative methods for academic work. The course is highly interactive\, emphasizing both the principles and skill development through applied activities. The course needs a minimum of 6 registrants and has an enrollment capacity of 10. \n\nDr. Monique Hennink is Professor in the Hubert Department of Global Health in the Rollins School of Public Health and Associated Faculty in Sociology at Emory University. She is also Visiting Professor at University of Michigan\, Department of Epidemiology\, and Instructor at the University of Columbia's EPISUMMER program in Epidemiology. She earned her PhD in Demography in the United Kingdom.\n\nDr Hennink was indicted into Emory’s MilliPub Club in 2023 and 2024 for two research papers. This honors faculty authors of a scientific publication with over 1\,000 citations - considered high impact scholarship. She received the 2020 Provost’s Distinguished Teaching Award for Excellence in Graduate and Professional Education at Emory University. She also received the 'Excellence in Research' Award in 2019 and the 'Excellence in Teaching' Award in 2016 at the Rollins School of Public Health.\n\nShe has particular expertise in applying qualitative research to examine public health issues. She has 30 years’ experience in the design\, conduct\, analysis\, and publication of qualitative health research. She has authored five textbooks on qualitative research\, including: Qualitative Research Methods 2nd edition (2020)\; Focus Group Discussions (2014)\, Qualitative Research Methods (2011) (also translated into Chinese) and International Focus Group Discussions (2007). She teaches graduate-level courses in qualitative research at Emory University. She developed the 'QUAL-WORKS' (https://sph.emory.edu/qual-works) training program in 2013 for public health professionals. Her courses\, workshops and books reflect the application of qualitative methods in globally diverse settings and provide guidance on how to balance methodological rigor with the practical realities of global research. She has also published on various methodological aspects of qualitative research\, such as using interpreters and translators in qualitative data collection\; the effect of using court reporters on data quality\; estimating sample size in qualitative studies\; and highlighting emerging methodological issues in focus group research. She has served as a board member for SAGE Publications on their ‘Cases in Methodology’ work and on the editorial board of the International Journal of Multiple Research Approaches. She co-chaired a three-year scientific panel for the International Union of the Scientific Study of Population (IUSSP)\, on ‘Qualitative Research in Population Studies’ which had a mandate to promote rigor in the use of qualitative methods in the discipline. She has led scientific sessions on qualitative research at key professional forums\, such as: International Congress of Qualitative Inquiry\; International Institute for Qualitative Methods\; European Association of Population Studies\; and the International Union for the Scientific Study of Population.\n\nTextbook Information: Hennink\, Hutter & Bailey (2020) 2nd Ed. Qualitative Research Methods. Sage Publications\; Ritchie et al (2014) Qualitative Research Practice: A Guide for Social Science Students & Researchers. Second Edition\; Emerson et al (2011) Writing Ethnographic Fieldnotes\; Rubin & Rubin (2012) Qualitative Interviewing. The Art of Hearing Data. Third Edition\; Hennink (2014) Focus Group Discussions. Oxford University Press
UID:148255-21903612@events.umich.edu
URL:https://events.umich.edu/event/148255
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Biomedical,Center For Political Studies,Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Graduate and Professional Students,Health,Health Data,Mathematics,Professional Development,Public Health,Research,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
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BEGIN:VEVENT
DTSTAMP:20260513T130729
DTSTART;TZID=America/Detroit:20260604T130000
DTEND;TZID=America/Detroit:20260604T150000
SUMMARY:Class / Instruction:June 2 - July 30\, 2026 T/TH  Course - Sampling in Practice
DESCRIPTION:June 2-July 30\, 2026\, T/TH\n1:00pm - 3:00pm\nA live course via Zoom. Registration and payment are required a minimum of two weeks prior to the start of the course.\n\nFounded in 1948\, the Summer Institute in Survey Research Techniques is designed specifically to meet the needs of professionals and graduate students seeking to deepen their expertise in survey methodology and data collection. Offered through the Michigan Program in Survey and Data Science within the Institute for Social Research at the University of Michigan\, the program provides a rigorous and flexible curriculum that blends theoretical foundations with practical application — entirely online.\n\nSampling in Practice\n\nUnlocking the art and science of sampling with an applied\, hands-on approach\, the course Sampling in Practice is designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming. Students will learn about probability sampling methods\, including simple random sampling\, stratification\, systematic selection\, cluster sampling\, probability proportional to size sampling\, and multistage sampling. We will also cover sampling cost models\, sampling error estimation techniques\, non-sampling errors\, missing data\, and nonprobability samples. The course emphasizes practical implementation\, featuring interactive coding exercises and in-class examples to reinforce each concept. A culminating project will give students the opportunity to integrate multiple techniques into a comprehensive sample design and demonstrate the profession in designing surveys\, selecting subjects\, analyzing sample data\, and solving real sampling problems using modern statistical tools.\n\nWhy take this course? \n\nThe course is crafted for students and practitioners eager: \n\nTo build proficiency in modern sampling techniques through active engagement and practical coding experience\nTo understand the basic ideas\, concepts and principles of probability sampling from an applied perspective\nTo be able to identify and appropriately apply sampling techniques to survey design problems\nTo understand and be able to assess the impact of the sample design on survey estimates\nTo be able to compute the sample size for a variety of sample designs\nTo learn how to design and select a probability sample involving complex sampling techniques in a survey project\, and receive expert feedback on a sampling report. \n\nYajuan Si is a Research Associate Professor in the Michigan Program in Survey and Data Science\, located within in the Institute for Social Research at the University of Michigan. She holds a Ph.D. in statistical science from Duke and received postdoctoral training at Columbia. Yajuan’s research focuses on methodology development\, from data analysis to study design\, in streams of Bayesian statistics\, linking design- and model-based approaches for survey inference\, data integration\, missing data analysis\, confidentiality protection\, and causal inference\, with applications in the social and health sciences. More information can be found here: https://websites.umich.edu/~yajuan/.
UID:148265-21903544@events.umich.edu
URL:https://events.umich.edu/event/148265
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Data,Data Analysis,Data Collection,Data Curation,Data Linkage,Data Management,Data Science,Graduate,Professional Development,Survey Methodology,Survey Methods,Survey Research
LOCATION:Off Campus Location
CONTACT:
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BEGIN:VEVENT
DTSTAMP:20260219T141559
DTSTART;TZID=America/Detroit:20260604T130000
DTEND;TZID=America/Detroit:20260604T150000
SUMMARY:Workshop / Seminar:Practice Behavior-Based Interviewing Using Virtual Reality
DESCRIPTION:Course details and registration are available on the Organizational Learning website.
UID:143106-21897772@events.umich.edu
URL:https://events.umich.edu/event/143106
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Communication,Human Resources,Professional Development
LOCATION:Center for Academic Innovation
CONTACT:
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BEGIN:VEVENT
DTSTAMP:20260515T091234
DTSTART;TZID=America/Detroit:20260604T130000
DTEND;TZID=America/Detroit:20260604T150000
SUMMARY:Social / Informal Gathering:Swap Shop 2nd Birthday Party
DESCRIPTION:The Lab Swap Shop\, launched in June 2024\, serves as a physical location where excess lab consumables\, glassware\, equipment\, and more can be rehomed within the U-M research community. Join us on June 4th from 1-3pm in room 5004 of the North University Building to celebrate a successful second year of the shop! Key milestones include more than a million dollars saved for U-M researchers and diversion of over 20\,000 pounds of supplies from the landfill. Bring the Swap Shop a birthday present of surplus lab supplies\, engage in creative reuse crafts\, take home a free air plant while supplies last\, and enjoy a slice of birthday cake! Check out our inventory to get an idea of available items!
UID:148300-21903825@events.umich.edu
URL:https://events.umich.edu/event/148300
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Research,Sustainability,Waste Reduction
LOCATION:1100 North University Building - 5004
CONTACT:
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BEGIN:VEVENT
DTSTAMP:20260522T140614
DTSTART;TZID=America/Detroit:20260604T140000
DTEND;TZID=America/Detroit:20260604T160000
SUMMARY:Presentation:Combinatorial Optimization Problems Arising from Graph-Based Models
DESCRIPTION:Abstract:\n\nWe propose and analyze several graph-defined combinatorial optimization problems inspired by multiple application areas.  \n\nFirst\, we consider an influence maximization model that uses the independent cascade approach\, but allows two types for packets of information\, +1 and -1. These represent the change in a receiver's sentiments on a product or belief on an empirical question (regarded as their \"bias\")\, which can be justified via Bayes' rule. The algorithmic problems we study may be viewed as taking a more fine-grained approach to traditional influence maximization problems\, and correspondingly exhibit non-trivial behavior even in the unbudgeted version where packets are unlimited—including tractability that depends on the probability parameters of the independent cascade dynamics. On the other hand\, we obtain NP-hardness results for the budgeted version more analogous to previous work. Several natural heuristics are shown to induce substantial reductions of bias in simulations with well-known social network datasets.  \n\nNext\, given an undirected graph representing similarities between a set of items and an additive measure evaluating them\, we treat the position of a special subset of items in an ordinal ranking through a collection of problems in which items may be combined if they are similar. The objective for these problems is to either maximize or minimize the absolute or relative rank of the special subset\, with a meta-goal of assessing the robustness of the rank\, even in the presence of a well-defined criterion. We classify the computational complexity of all four problems\, mostly finding worst-case hardness\, then find exact and approximate solutions to special cases and variants of the problems. These structured cases are inspired by numerous real-world examples and may be used to assess commonly cited facts across disparate domains\, as we demonstrate for sources of greenhouse gas emissions that contribute to climate change. We then adapt our framework to require subsets of comparable measure\, converting the above ranking problems into redistricting problems\, with analogues to the former's grid variants. Emphasis is placed on worst-case deviations from proportional representation and an urban-rural model in which gerrymandering ability is curtailed.
UID:148410-21904197@events.umich.edu
URL:https://events.umich.edu/event/148410
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Dissertation,Graduate,Graduate Students,Mathematics
LOCATION:East Hall - 4088
CONTACT:
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