We are a group of motivated Canadian Public Servants who want to get our feet wet with Bayesian analysis and probabilistic programming. This website will serve as an easily-accessible repository of course material, syllabus, references, etc.

Join us by WebEx (password required).

Bayesian Statistics

Here's a short-ish explanatory video of Bayesian analysis:

Bayesian analysis is particularly useful when:

  • You have prior beliefs about unknown model parameters or explicit information about data generation — i.e., useful info you want to incorporate
  • You have few data or many unknown model parameters and it is hard to get an accurate result with your data alone (without the added structure or information)
  • You want to capture the uncertainty about your result — how sure or unsure your model is — instead of only a single “best” result

Course Plan

Tentative syllabus

Based on multiple suggestions, we'll be following John Krushke's Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan (2nd edition) book.

This study group will meet weekly, and consist of two parts:

  1. Reading the chapters individually before each session, and
  2. Meeting for 1h every week to go through exercises together.

We might lump some a few of the introductory chapters for the first weeks. We'll end up using both Python and R.


The plan is for participants to collaboratively perform directed sessions together as a study group, either by webcam or in person. We are partnering with the Canadian School of Public Service's Digital Academy for services and a boardroom to meet in person. Check the links on the left to access the details on how to communicate with the group.