{"id":182,"date":"2019-02-25T16:56:11","date_gmt":"2019-02-25T16:56:11","guid":{"rendered":"https:\/\/www.allendowney.com\/blog\/?p=182"},"modified":"2019-02-25T16:56:18","modified_gmt":"2019-02-25T16:56:18","slug":"bayesian-zig-zag-webinar","status":"publish","type":"post","link":"https:\/\/www.allendowney.com\/blog\/2019\/02\/25\/bayesian-zig-zag-webinar\/","title":{"rendered":"Bayesian Zig-Zag Webinar"},"content":{"rendered":"\n

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<\/a>“. Eric Ma<\/a> served as moderator, introducing me and joining me to answer questions at the end.<\/p>\n\n\n\n

The example I presented is an updated version of the Boston Bruins Problem, which is in Chapter 7 of my book, Think Bayes<\/a><\/em>. At the end of the talk, I generated a probablistic<\/g> 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.<\/p>\n\n\n\n

Does that mean I was right? Maybe<\/a>.<\/p>\n\n\n\n

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 \ud83d\ude42<\/p>\n\n\n\n

If you did not watch it live, you can view the recorded webinar<\/a> at no cost other than registering and providing contact information.<\/p>\n\n\n\n

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

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. <\/p>\n","protected":false},"excerpt":{"rendered":"

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…<\/p>\n

Read More Read More<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[1],"tags":[9,10,11],"class_list":["post-182","post","type-post","status-publish","format-standard","hentry","category-uncategorized","tag-bayesian","tag-poisson-process","tag-webinar"],"yoast_head":"\nBayesian Zig-Zag Webinar - Probably Overthinking It<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.allendowney.com\/blog\/2019\/02\/25\/bayesian-zig-zag-webinar\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Bayesian Zig-Zag Webinar - Probably Overthinking It\" \/>\n<meta property=\"og:description\" content=\"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“. 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