3.00 Credits
Selective course focused on Bayes theorem, conjugate priors, posterior distributions, credible intervals, Monte Carlo approximations, Markov chain Monte Carlo (MCMC) methods, Gibbs sampling, Metropolis-Hastings algorithm, Bayesian hypothesis testing, hierarchical modeling, linear regression, and logistic regression. Preq: Students are expected to have completed a course in introductory probability and a course in introductory statistics, and have some experience with the software R before enrolling in this course.