Overview
Overview
Regression Discontinuity Design Analysis
is a statistical technique used to evaluate the effect of a policy change or intervention. It is particularly useful for evaluating causal relationships in situations where randomization is not possible. This method is often employed in program evaluation and policy analysis. The technique relies on the assumption that the treatment effect is constant across the discontinuity point. It is typically used by researchers and policymakers who need to assess the impact of a specific event or intervention. By understanding regression discontinuity design analysis, you can gain valuable insights into the effects of policy changes and interventions.
Regression Discontinuity Design Analysis is a powerful tool for understanding the impact of policy changes on individuals and societies. This course teaches you how to harness the potential of Regression Discontinuity Design (RDD) to analyze the effects of discontinuities in treatment assignment. By mastering RDD Analysis, you'll gain a deeper understanding of how policies can shape outcomes and make data-driven decisions. With this course, you'll learn key concepts, including Instrumental Variables (IV) estimation and Confounding Variable Control. Upon completion, you'll be equipped with the skills to drive business growth, inform public policy, and advance your career in data science and analytics.