Kurs-Information

The aim of this course is to understand the practical and theoretical foundations of Bayesian statistics as well as recent developments in Bayesian computation including the implementation of these approaches in statistical software using appropriate numerical procedures. Treated topics include: Bayes’ Theorem, normal prior and likelihood, conjugate prior distributions, posterior inference, Bayesian regression models, hierarchical models, Gibbs sampling, MCMC, Variational Bayes.