Bayesian Regression: Theory & Practice

Background: Think like a Bayesian - Samples and data-generating processes

This section provides a quick recap of fundamental concepts of Bayesian Data Analysis and the technical work flow this course uses.

In the first part, we explore how to think like a computational Bayesian, which is to think in terms of data-generating models and sampling processes. To get more familiar with the mode of being, there are examples using the probabilistic programming language WebPPL.

The second part introduces basics of data wrangling (in the tidyverse) and plotting (with ggplot2).