ICPSR Summer Program courses & scholarships
2019 ICPSR Summer Program in Quantitative Methods of Social Research
Founded in 1963, the ICPSR Summer Program offers rigorous, hands-on training in statistics, quantitative methods, and data analysis for students, faculty, and researchers of all skill levels and backgrounds. The ICPSR Summer Program is world-renowned for its premier quality of instruction, fun learning environment, and unparalleled networking opportunities.
For those needing to learn a specific methodological technique in just a few days, the Summer Program offers more than 40 short workshops, including:
- Social Science Data and Model Visualization in R (May 16-17, Houston)
- Group-based Trajectory Modeling for the Medical and Social Sciences (May 22-24, Ann Arbor)
- Advanced Multilevel Modeling with HLM (May 28-31, Amherst)
- Multilevel Modeling with HLM and SPSS (June 3-7, Amherst)
- Latent Growth Curve Models (LGCM): A Structural Equation Modeling Approach (June 3-7, Chapel Hill)
- Growth Mixture Models: A Structural Equation Modeling Approach (June 10-12, Chapel Hill)
- Introduction to Mixed Methods Research (June 12-14, Chapel Hill)
- Analyzing Intensive Longitudinal Data: A Guide to Diary, Experience Sampling, and Ecological Momentary Assessment Methods (June 24-28, Amherst)
- Statistical Methods for Sociogenomics and Behavioral Epigenomics (July 1-3, Salt Lake City)
Held at the University of Michigan, the Summer Program’s Four-week Sessions provide an immersive learning experience—think “summer camp for social scientists”! Participants in our First (June 24 - July 19) and Second (July 22 - August 16) Sessions can choose from more than 40 courses, including regression, Bayesian analysis, longitudinal analysis, game theory, MLE, SEM, causal inference, machine learning, multilevel models, race/ethnicity and quantitative methods, and more.
Scholarships are available for students in psychology, sociology, public policy, and education. Scholarships are also available to graduate students from under-represented groups.