Registration Open for ICPSR Summer Program in Quantitative Methods

DABS: DATA AND BIOINFORMATION STUFF

Registration Open for ICPSR Summer Program in Quantitative Methods

ICPSR Summer Program logo

Improve your statistical analysis skills with ICPSR’S Summer Program!

ICPSR (Inter-university Consortium for Political and Social Research), is home to the world’s largest collection of digital social science data. Register now for ICPSR’s long-running and well-respected Summer Program in Quantitative Methods. This program offers a mix of intensive four-week sessions, shorter workshops, and lectures series throughout the summer This year’s program is hybrid with opportunities for virtual attendance or on-location attendance in Ann Arbor, MI. Courses are for beginning or advanced students of quantitative methods. The program attracts university faculty and researchers, graduate students, and nonacademic research scientists.

As members of ICPSR, the UMB community receives a significant discount on tuition. There are also a number of scholarships available to help defray costs even further. 

Example workshop topics include:

  • Race, Ethnicity, and Quantitative Methodology
  • Regression Analysis
  • Multivariate Statistical Methods: Advanced Topics
  • Machine Learning: Applications in Social Science Research
  • Data Science and Text Analysis
  • Panel Data and Longitudinal Analysis
  • Bayesian Modeling

Important dates:

  • Scholarship Deadline: March 28, 2022
  • Early Registration Discount Deadline: April 30, 2022
  • Registration closes for Session 1: June 12, 2022
  • Registration closes for Session 2: July 10, 2022
  • Session 1: June 20 – July 15, 2022
  • Session 2: July 18 – August 12, 2022
  • Short Workshops: Multiple dates from May through August 2022.

Questions? Contact: Amy Yarnell, data services librarian, and Jean-Paul Courneya, bioinformationist, at data@hshsl.umaryland.edu.


The Center for Data and Bioinformation Services (CDABS) is the University of Maryland Health Sciences and Human Services Library hub for data and bioinformation learning, services, resources, and communication

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