SOAN 219 - Applied Bayesian Regression for the Social Sciences

FDR: SC Science, Math, CS Distribution
Credits: 3

This course is an introduction to applied Bayesian regression, emphasizing applications for social scientists. We begin by introducing some philosophical and mathematical bases of Bayesian inference. We then move on to a sustained focus on applied regression, starting with bivariate regression and moving on to regression with multiple predictors, up to and including models with interactions. Along the way, students will be exposed to the use of directed acyclic graphs (DAGs) in thinking about causality with observational data. Throughout the course students will carry out numerous analyses of data, learning by doing. Examples are drawn from anthropology, sociology, political science, and related fields.