Chuck Huber: Introduction to Bayesian Statistics Using Stata

This talk will provide an intuitive introduction to the concepts of Bayesian analysis and demonstrate how to fit Bayesian models using Stata.  No prior knowledge of Bayesian analysis is necessary and specific topics will include the relationship between likelihood functions, prior, and posterior distributions,  Markov Chain Monte Carlo (MCMC) using the Metropolis-Hastings algorithm, and how to use Stata's Bayes prefix to fit Bayesian models.