Bayesian Data Analysis

3 credits · Graduate School

This course introduces the methodology and rationale for Bayesian methods and their applications. Topics include the historical development of Bayesian methods such as hierarchical models, Markov Chain Monte Carlo (MCMC) and related sampling methods, specification of priors, sensitivity analysis, and model checking and comparison. This course features applications of Bayesian methods to biomedical research. Prerequisites: BIOS 6312 and BIOS 6342. [3]