Data Analysis for Policy Research Using

Prerequisites: Instructor-Managed Waitlist, Course Application, and SIPAU6501 - Quantitative Analysis II. This course will develop the skills to prepare, analyze, and present data for policy analysis and program evaluation using R. In Quant I and II, students are introduced to probability and statistics, regression analysis and causal inference. In this course we focus on the practical application of these skills to explore data and policy questions on your own. The goal is to help students become effective analysts and policy researchers:  given available data, what sort of analysis would best inform our policy questions? How do we prepare data and implement statistical methods using R? How can we begin to draw conclusions about the causal effects of policies, not just correlation? We’ll learn these skills by exploring data on a range of policy topics: COVID-19 cases; racial bias in NYPD subway fare evasion enforcement; the distribution of Village Fund grants in Indonesia; US police shootings; wage gaps by gender/race; and student projects on topics of your choosing.