Bayesian Statistical Modeling and Data Analysis

Catalog description

Principles of data analysis and advanced statistical modeling. Bayesian inference, prior and posterior distributions. Linear, multivariate, and multi-level models. Model checking and selection. Stochastic simulation by Markov Chain Monte Carlo. Prerequisites: Regression (STA 221L) and Statistical Inference (STA 332). Not open to students with credit for STA 360L, STA 602L, or STA 702L.