Introduction

This repository contains Python translations of the examples from Georgia Tech’s ISYE 6420: Bayesian Statistics, created by Professor Brani Vidakovic and currently taught by Professor Roshan Joseph. It also includes notes on each lecture.

Why?

We created this site to address some of the most common student complaints and questions. The most frequent source of dissatisfaction was the course’s use of OpenBUGS, so we redid the lecture examples in Python and PyMC.

We also want to supplement the lectures by adding notes that address common questions and provide links for further reading on specific subjects. As an overview course, this class doesn’t go too deep on any one topic, but we hope to provide a jumping-off point for students who are interested in going further.

Site structure

This site was built with Jupyter Book and is made up of a combination of Markdown files and Jupyter notebooks. You can download the source for any page in the upper right, or view the entire repository on Github.

All pages match a corresponding lecture on Canvas, except when there are more pages than lectures in a unit, in which case the additional pages will be at the end of the unit. For example, there are only eight lectures in Unit 3 on Canvas. The first eight pages here match the lecture numbers, while the ninth and tenth pages are supplementary problems.

Any necessary data will either have a download link or, if the data is compact enough, will be included in the code.

Contributors

Aaron Reding, current head TA, started taking notes on the lectures and working on PyMC versions of the code as a student in Spring 2020, eventually using those materials to create this site.

Greg Schreiter was the head TA for several years and wrote many of the problem solutions as well as compiling the course errata.

Jason Naramore, a current TA, has contributed Python code, exercise solutions, and lecture notes.

Former students Amanuel Anteneh and Anthony Miyaguchi have contributed code and notes.

Thank you to everyone who has contributed, both directly and indirectly by asking great questions on the class discussion forums.