GOV 385L • Bayesian Statistics
9:30 AM-12:30 PM
This Course will provide and introduction to Bayesian statistics and its applications in political science. Topics will include differences between Bayesian and frequentist approaches to point estimation, inference and hypothesis testing. Computational methods such as Markov chain Monte Carlo techniques will also be covered as well as other topics such as hierarchical modeling and ideal point estimation techniques. Students taking this course should have firm understanding of standard statistical methods including point estimation and hypothesis testing, Linear regression, generalized linear models and maximum likelihood methods. Prospective students who are unsure about these prerequisites should contact the professor.