In this blog post, we provide an accessible introduction to Regression Discontinuity Design (RDD)—a powerful quasi-experimental method for causal inference when treatment assignment is based on a cutoff. Using simulated data and step-by-step Python code, you’ll learn how to estimate the treatment effect at the cutoff, construct confidence intervals, and visualize local linear regressions.