To balance frequentist ideas that dominate most undergraduate statistics education the course provides
exposure to Bayesian methods. With advances of computational tools it is shown that Bayesian methods are no longer
of limited practical use. The implementation Markov chain methods for sampling from the posterior is presented
and thus demonstrating that Bayesian methods are possible, even in very complicated models.