Bayesian Regression: Theory & Practice

This site provides material for an introductory-level course on Bayesian linear regression modeling. The course presupposes some prior exposure to statistics and some acquaintance with R.

Intended audience

This course is offered to students (both under-graduate and graduate) of (computational) linguistics and cognitive science.

Scope

The course introduces the basics of Bayesian data analysis, and then immedidately zooms in on regression modeling. Starting with simple linear regression, we want to reach a basic understanding of hierarchical generalized linear models.

Additional material

An even more basic introduction to data analysis (introducing R, tidyverse, Bayesian and, eventually, also frequentist statistics) is the webbook “An introduction to Data Analysis”.

Acknowledgements

Part of this material was used in a previous course, co-taught with the great Timo Roettger. I’m recycling some of his material here, but have (in full awareness of the catastrohpe) made it more dry, less insightful and more nerdy to conceal the breach of authorship.