This is the last video of a three part introduction to Bayesian data analysis aimed at *you* who isn’t necessarily that well-versed in probability theory but that do know a little bit of programming. If you haven’t watched the other parts yet, I really recommend you do that first: Part 1 & Part 2.

This third video covers the *how?* of Bayesian data analysis: How to do it efficiently and how to do it in practice. But *covers* is really a big word, *briefly introduces* is really more appropriate. Along the way I will then *briefly introduce* Markov chain Monte Carlo, parameter spaces and the computational framework Stan: