<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Maximum Likelihood on Adventures in Why</title><link>https://www.adventuresinwhy.com/tag/maximum-likelihood/</link><description>Recent content in Maximum Likelihood on Adventures in Why</description><generator>Hugo</generator><language>en-us</language><managingEditor>bob@ConvexAnalytics.com (Bob Wilson)</managingEditor><webMaster>bob@ConvexAnalytics.com (Bob Wilson)</webMaster><copyright>&amp;copy; Bob Wilson {year}</copyright><lastBuildDate>Tue, 04 Jan 2022 00:00:00 +0000</lastBuildDate><atom:link href="https://www.adventuresinwhy.com/tag/maximum-likelihood/index.xml" rel="self" type="application/rss+xml"/><item><title>The Winner's Curse: Why it Happens and What to Do About It</title><link>https://www.adventuresinwhy.com/post/point_estimates/</link><pubDate>Tue, 04 Jan 2022 00:00:00 +0000</pubDate><author>bob@ConvexAnalytics.com (Bob Wilson)</author><guid>https://www.adventuresinwhy.com/post/point_estimates/</guid><description>When running an A/B test with many variants, say, more than 5, we often run into a phenomenon known as the Winner&amp;rsquo;s Curse, where the winning variant performs worse when we adopt it universally than it had during the test itself. In this post, we discuss why this phenomenon occurs and what to do about it.</description></item><item><title>Contingency Tables Part IV: The Score Test</title><link>https://www.adventuresinwhy.com/post/score_test/</link><pubDate>Tue, 24 Nov 2020 00:00:00 +0000</pubDate><author>bob@ConvexAnalytics.com (Bob Wilson)</author><guid>https://www.adventuresinwhy.com/post/score_test/</guid><description>The score test can be used to calculate p-values and confidence intervals for A/B tests. The score test considers the slope of the likelihood function at the parameter value associated with the null hypothesis.</description></item><item><title>Sprinkle some Maximum Likelihood Estimation on that Contingency Table!</title><link>https://www.adventuresinwhy.com/post/contingency-tables-mle/</link><pubDate>Sun, 08 Nov 2020 00:00:00 +0000</pubDate><author>bob@ConvexAnalytics.com (Bob Wilson)</author><guid>https://www.adventuresinwhy.com/post/contingency-tables-mle/</guid><description>Maximum Likelihood Estimation provides consistent estimators, and can be efficiently computed under many null hypotheses of practical interest.</description></item></channel></rss>