Applied Bayesian Statistics provides you with an introduction to the Bayesian framework in statistics, including the differences between Bayesian approaches and the more standard frequentist approach. It will cover basic single and multi-parameter models, regression, Bayesian estimation (including MCMC simulation techniques) and hierarchical models. You will be introduced into Bayesian modelling through the use of the R programming language and JAGS as computational tools. The emphasis in the course is on encouraging you to apply Bayesian methods in various environments including business and health sciences.