The Data and Policy Summer Scholar Program is offered twice during the summer. The two online sessions are identical. Participants can apply to the session that best fits their schedule.

Program Dates

  • Session One | June 21 - August 6, 2021
  • Session Two | August 2 - September 17, 2021

Schedule Structure

The virtual program is a combination of asynchronous lectures and synchronous office hours with faculty and graduate teaching assistants from anywhere in the world. 

Students can anticipate a commitment of approximately 12-18 hours per week. 

  • 5-8 hours of lectures, watched and re-watched at your own pace
  • 3-5 hours of assignments and projects
  • 1-2 hours of live office hours with faculty and teaching assistants
  • 2-3 hours of live sessions of community resources 

The weekly time commitment will vary per student based on their own learning pace. Previous students completed DPSS while maintaining employment, internships and other academic coursework.  

The live office hours and sessions will accommodate our student time zones and occur at various times throughout the week. You can anticipate live office hours and activities to occur in the morning and evening of Central Daylight Time (Chicago Time, UTC-6).

Review our FAQ for more information. 

Example Program Schedule

Week/Module Data Analytics  Programming in R UChicago and Program Resource Sessions
Week 1 Course Preview Course Preview  Program Welcome Orientation

Week 2

1.1 - Foundations of Causal Inference for Public Policy 2.1 - Intro to R and RStudio (working dirs, projects, panes, R basics, etc)

 Policy-in-Action Speakers

1.2 - Mean, Variance, Random Variables, and Samples 2.2 - Intro to tidyverse, fundamentals of data, basic visualization;

Week 3

1.3 - Difference in means: RCTs (experimental ideal) 2.3 - Tidy data, data wrangling, and simple data cleaning

 Career Exploration Workshops

1.4 - Bivariate regression: properties, testing, interpretation 2.4 - Recoding, data transformation, and joins (plus more wrangling)

Week 4

1.5 - Multivariate regression: testing, interpretation, omitted variable bias 2.5 - Data visualization and exploration (ggplot2, summarization)

 Graduate Admissions Panel

1.6 - Binary outcomes and functional form 2.6 - APIs and policy applications (working with Census data)

Week 5

1.7 - Panel data designs: fixed effects, first differences 2.7 - Programming concepts (for loops, functions, control flow)

 Virtual Chats with UChicago student and alumni

1.8 - Difference in Differences Design 2.8 - Causal inference stats in R (lm, sample, distributions, stargazer)

Week 6

1.9 - Regression discontinuity designs 2.9 - Introduction to spatial data (sf, tmap, ggmap)  Writing in Policy Workshops
1.10 - Instrumental variables 2.10 - Literate programming (RMarkdown, code syntax), GitHub

Week 7

Capstone Research Project
3.1 - Capstone Project Kick-off Meeting
3.2 - Policy Memo Writing Workshop
3.3 - Capstone Working Group
3.4 - Capstone Mid-cycle Check Meeting
3.5 - Capstone Presentation Summit