STAT820 Bayesian Statistics
This course will take an applied approach to doing Bayesian data analysis. We will begin with an introduction to Bayesian probability and reasoning (contrasting this with the conventional approach to statistical analysis relying on null hypothesis significance testing) and an overview of Markov chain Monte Carlo (MCMC) algorithms that enable contemporary Bayesian data analysis. Following this, the rest of the course will be oriented towards understanding and performing statistical techniques that students will use in their own individual research projects. The final assignment for the course will be an empirical study suitable for (eventual) publication, and students are encouraged to have (or collect) data to use for analysis in the course (and should have IRB approval before the course). Consultation with the course instructor prior to the start of the course is recommended for students who are unsure of what data they can/should use. Prerequisite: MTHD808, STAT809, STAT810 or with instructor permission under special circumstances.