Introduction to Bayesian Computing and Statistics

(3 Credit Hours) · Undergraduate

This course introduces fundamental concepts of Bayesian statistics and illustrates how to apply them to various areas of scientific research. Probabilistic programming languages (WinBugs, JAGS and/or Stan) are introduced, and their interfaces to the statistical computing and graphics environment R are discussed. These languages are used, either directly or via their R interface, to fit statistical models within a Bayesian framework to real-world examples from many disciplines such as engineering, science (e.g. agricultural, biological, environmental, medical and physical), social sciences, economics, finance and astronomy.