In recent decades, there has been an explosion of interest in Bayesian methodologies in the sciences. There are several reasons for this recent interest: first, Bayesian methods often yield easier-to-interpret answers to statistical questions than classical methods; and second, Bayesian methods are applicable in situations where classical methods are difficult or impossible to implement. In this course, you will learn the basics of practical Bayesian data analysis. course start date- 8 august

The course will begin with the theory behind Bayesian data analysis, and move toward simple, common models in the social sciences, like t tests, ANOVA, and regression. From there, we will learn about more complicated models and how these may be fit to the data. Special attention will be given to Markov Chain Monte Carlo (MCMC) methods, which give Bayesian methods their immense flexibility and power. Using software, the power of MCMC methods are available to researchers who are not specialists in Bayesian methods. This class will give you the tools to fit a wide variety of models easily, though the use of the WinBUGS software.