Bayesian Statistics Using R

Bayesian approach is becoming increasingly popular in all fields of data analysis, including but not limited to epidemiology, ecology, economics, and political sciences. It also plays an increasingly important role in data mining and deep learning.

This program provides a practical introduction to applied Bayesian data analysis, combining theory, philosophy and computational facility with the emphasis on formulating and answering real life questions. The two courses provide a broad overview of the fundamentals of Bayesian inference via clear practical examples and may serve as a stepping stone towards any other, more specialized, topic in Bayesian statistics.

Learn the fundamentals of Bayesian approach to data analysis, and practice answering real life questions using R.

Now that you know the basics of Bayesian inference, dive deeper to explore its richness and flexibility more fully. Let’s take a closer look at modeling latent variables, Bayesian model averaging, generalised linear models, and MCMC methods