EPSY 941 Bayesian Statistics
The purpose of this course is to acquaint advanced quantitative students with the fundamentals of Bayesian data analysis. The goals of the class are to introduce Bayesian inference, starting from the philosophical perspective, and provide methods for implementing Bayesian analysis for a variety of different statistical models. Class time is balanced between theoretical perspectives and practical applications. Topics covered include: a review of basic probability, Bayes' rule, probability distributions, Markov Chain Monte Carlo (MCMC) estimation and software for its implementation, and applications of MCMC to a variety of statistical models. Prerequisite: EPSY 905 or equivalent or consent of instructor.