Bayesian Zig-Zag Webinar

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