Spring 2023 - 61325 - PA 397 - Introduction to Empirical Methods for Policy Analysis

This course develops foundational skills in problem solving and fundamental quantitative methods (data analysis, statistical inference, quantitative models for decision making) applied to public policy analysis and management. Most of the contents of this course will be focused on the questions surrounding causal inference. First, we will use a descriptive approach to cover the fundamentals of statistical analysis and probability, and then we will turn into the tools of inferential analysis: their logic, procedures, and limitations. Topics covered in this class include experimental and quasi-experimental designs, measures of central tendency and dispersion, frequency and probability distributions, hypothesis testing, linear correlation and simple linear regression, multiple linear regression, risk in decision making, decision trees, expected utility, effect sizes, power analysis and meta-analysis. The course is delivered through weekly lectures which combine theory and practice, and a weekly discussion lab focused on applications and problem solving.