BIOS 9231

Bayesian Statistics I: 3-0-3

This course provides the student with an introduction Bayesian Analysis and compares Bayesian methods to that of frequentists. The course includes selection of prior distributions, computing posterior distributions, conjugate models, Beta-Binomial model, Normal-Normal model, and Gamma-Poisson model. Bayesian inference using point and interval estimation, Bayesian hierarchical models, and exchangeability will be explored. Topics including Empirical Bayes versus a fully Bayes approach, Markov Chain Monte Carlo methods and model checking using Bayes factors and sensitivity analyses will be included. Prerequisite: A minimum grade of "B" in BIOS 9131.