00-background.qmd

---
title: "Bayesian Regression: Theory & Practice"
subtitle: "Background: Think like a Bayesian - Samples and data-generating processes"
author: "Michael Franke"
---

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](http://webppl.org/).

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