{"id":883,"date":"2023-03-20T18:56:27","date_gmt":"2023-03-20T18:56:27","guid":{"rendered":"https:\/\/www.allendowney.com\/blog\/?p=883"},"modified":"2023-03-20T20:35:48","modified_gmt":"2023-03-20T20:35:48","slug":"the-bayesian-killer-app","status":"publish","type":"post","link":"https:\/\/www.allendowney.com\/blog\/2023\/03\/20\/the-bayesian-killer-app\/","title":{"rendered":"The Bayesian Killer App"},"content":{"rendered":"\n

It’s been a while since anyone said “killer app” without irony, so let me remind you that a killer app is software “so necessary or desirable that it proves the core value of some larger technology,” quoth Wikipedia<\/a>. For example, most people didn’t have much use for the internet until the world wide web was populated with useful content and the first generation of browsers made it easy to access.<\/p>\n\n\n\n

So what is the Bayesian killer app? That is, for people who don’t know much about Bayesian methods, what’s the application that demonstrates their core value? I have a nomination: Thompson sampling<\/a>, also known as the Bayesian bandit strategy, which is the foundation of Bayesian A\/B testing.<\/p>\n\n\n\n

I’ve been writing and teaching about Bayesian methods for a while, and Thompson sampling is the destination that provides the shortest path from Bayes’s Theorem to a practical, useful method that is meaningfully better than the more familiar alternative, hypothesis testing in general and Student’s t<\/em> test in particular.<\/p>\n\n\n\n

So what does that path look like? Well, funny you should ask, because I presented my answer last November as a tutorial at PyData Global 2022<\/a>, and the video has just been posted:<\/p>\n\n\n\n

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