On February 13 I presented a webinar for the ACM Learning Center, entitled “The Bayesian Zig Zag: Developing Probabilistic Models Using Grid Methods and MCMC“. Eric Ma served as moderator, introducing me and joining me to answer questions at the end.

The example I presented is an updated version of the Boston Bruins Problem, which is in Chapter 7 of my book, Think Bayes. At the end of the talk, I generated a probablistic prediction for the Bruins’ game against the Anaheim Ducks on February 15. I predicted that the Bruins had a 59% chance of winning, which they did, 3-0.

Does that mean I was right? Maybe.

According to the good people at the ACM, there were more than 3000 people registered for the webinar, and almost 900 who watched it live. I’m glad I didn’t know that while I was presenting 🙂

If you did not watch it live, you can view the recorded webinar at no cost other than registering and providing contact information.

Here are the slides I presented. And here is a static view of the Jupyter notebook with all of the code and results. You can also run the notebook on Binder.

Thanks to the ACM Learning Center for inviting me, to Eric for moderating, and to Chris Fonnesbeck and Colin Carroll for their help developing the example I presented.