Introduction to Bayesian Statistics for Social Scientists

This course will familiarise students with the basic concepts of Bayesian theory. It is designed to provide an introduction to the principles, methods, and applications of Bayesian statistics. Bayesian statistics offers a powerful framework for data analysis and inference, allowing for the incorporation of prior knowledge and uncertainty in a coherent and systematic manner.

The course covers:

• The Basics of Probability
• Bayes’ Theorem and Bayesian inference
• Probability Functions
• Bayesian Conjugates
• Markov Chain Monte Carlo
• Applications

By the end of the course participants will:

• Be able to understand the basics of Bayesian analysis
• Perform simple Bayesian analyses
• Apply simple models to their own work

The course will be split across two days. On both days, participants will work through a two-hour pre-recorded lecture in the morning and attend a two-hour live session at 2pm where they will have the opportunity to apply their learning to practical examples.