https://at-ceu.studyguide.timeedit.net/modules/DOPP5078?type=COREThis course explores the role of causal inference methods and data in evidence-based policymaking. Using the statistical software R, students will be introduced to key methods of causal inference used in program and policy evaluation. Through the use of case studies, the course emphasizes the practical application of these evaluation techniques.Students need to have a beginner's familiarity with R before the start of the course (see helpful materials below for getting started). The course begins with a gentle introduction to R, followed by the potential outcomes and the causal graph framework to develop an understanding of causality. Topics covered include experiments (RCTs), difference-in-differences, co-variate adjustment through regressions, and matching.Session format: Short lecture on the concepts followed by lab work with R.Part of Quantitative Policy Analysis specialization for MAPP and MPA.