Political methodology is a rapidly changing and fascinating subfield of political science. From text analysis to scaling models to network models to machine learning nethods, political science sits at the forefront of applied statistical research on several fronts. This course will cover the foundations necessary to work at the fronteir of political methodology, and then we will move through selected topics. The course is not defined by Bayesian analysis so much as it is unified by it: we will work through a number of examples and methods within a Bayesian framework, always with an eye to substantive insight into political processes.

Previously offered 2015, 2016, 2021.