(Same as PUBLPOL 303B and IPS 205B). After developing/reviewing some statistical background material, the course focuses on the most essential and widely used statistical research tools for public policy analysis, including multiple regression analysis, multilevel modeling and Bayesian analysis. These tools provide vital background for a wide variety of professional pursuits - not only engaging in policy analysis in government, research institutes, and academic settings, but also handling complex empirical issues in litigation, investment banking, consulting or finance. Topics include hypothesis testing, regression specification, logistic regression, probit, heteroscedasticity, serial correlation, errors in the variables, instrumental variables, simultaneous equations, generalized linear models, simulation, model checking, causal inference, and missing data imputation. Extensive hands-on experience with empirical analysis via computer exercises using popular statistical packages is a key component of the course. The skills developed are critical for becoming an intelligent consumer or producer of empirical research. The course is designed to be accessible to students with widely varying backgrounds in statistics or econometrics. Students who desire a more mathematical treatment of the topics may take the two unit "Econometrics: Mathematical Methods" supplement (Law 367) concurrently. A knowledge of basic statistics at the level of QM: Statistical Inference is a prerequisite.