An Applied Introduction to Bayesian Methods (Chapel Hill, NC)


The use of Bayesian methods has increased rapidly in many social science fields over the past two decades. Bayesian analysis is well-grounded in probability theory, can often better account for the complexity of social processes, can improve computational efficiency, and even allows researchers to systematically include their own expertise and/or qualitative evidence in the quantitative framework of a statistical model. This course will provide an introductory overview of Bayesian methods as they are applied to social science research. We will focus on the two complementary goals of learning the theory behind Bayesian inference as well as practical implementation of several common models in R.

No prior knowledge of Bayesian methods is necessary. However, this is not simply a survey course. Participants will walk away from the course with an understanding of how to apply Bayesian models to their own research as well as knowledge of what is going on "under the hood" with their results. Class time will be spent in lecture and working hands-on with example data in R.

Fee: Members = $1300; Non-members = $2600

Tags: bayes, bayesain methods

Course Sections