Bayesian statistics offer flexible techniques for researchers who cannot properly analyze their data using methods based on classical statistics. This course will provide a sound basis in Bayesian statistics for those who want to:

• understand what Bayesian statistics is about;
• use Bayesian statistics to build and evaluate statistical models; 
• get hands on experience with Bayesian statistics in Openbugs, R, JAGS, and Bain.

This 4 day course zooms in on the key concepts of Bayesian Statistics and advanced techniques for data-analysis. Topics that are covered include: Bayes’ theorem, Gibbs sampling, the Metropolis-Hastings algorithm, the Bayes factor, the evaluation of informative hypotheses, Bayesian methods for linear regression, moderation, and mediation, and data-analysis in OpenBUGS or R and JAGS. 

The course is aimed at researchers who not only work with statistical tools, but are also interested in the development and evaluation of statistical tools. Among these are psychometricians, sociometricians, epidemiologists, and statisticians. The only requirement is familiarity with the following concepts: the likelihood function, the p-value, analysis of variance, and multiple regression.