This unit provides a thorough introduction to the concepts and methods of modern Bayesian statistical methods with particular emphasis on practical applications in biostatistics. Comparison of Bayesian concepts involving prior distributions with classical approaches to statistical analysis, particularly likelihood based methods. Applications to fitting hierarchical models to complex data structures via simulation from posterior distributions using Markov chain Monte Carlo techniques (MCMC) with the WinBUGS software package. -- Course Website
Instructor: A/Prof Lyle Gurrin
Prerequisites: MPH5040, EPM5002, EPM5003, EPM5004, EPM5009 and EPM5014
