Applied Statistics
This course advances students’ understanding of statistical modeling for policy research, emphasizing econometric approaches to causal inference with observational data. Students examine the theoretical connections among econometrics, biostatistics, psychometrics, and machine learning while focusing on applied methods suited to policy contexts with limited experimental data.
Topics include nonlinear models, transformations, model selection, and multi-part modeling strategies used in fields such as health economics. By the end of the course, students apply advanced statistical tools to analyze complex data sets and evaluate causal relationships that inform evidence-based policy decisions.
Note: This course is only open to MPhil/PhD students.
