<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Bayesian on Aneesh Sathe</title><link>https://aneeshsathe.com/tags/bayesian/</link><description>Recent content in Bayesian on Aneesh Sathe</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Sun, 05 Jan 2025 00:30:49 +0000</lastBuildDate><atom:link href="https://aneeshsathe.com/tags/bayesian/index.xml" rel="self" type="application/rss+xml"/><item><title>Jan 4, 2025</title><link>https://aneeshsathe.com/jan-4-2025/</link><pubDate>Sun, 05 Jan 2025 00:30:49 +0000</pubDate><guid>https://aneeshsathe.com/jan-4-2025/</guid><description>&lt;h4 id="bayesian-thinking-talk-youtube"&gt;
&lt;a href="https://www.youtube.com/watch?v=woPMK670idc"&gt;Bayesian Thinking Talk (youtube)&lt;/a&gt;
&lt;a href="#bayesian-thinking-talk-youtube" class="heading-anchor"&gt;#&lt;/a&gt;
&lt;/h4&gt;
&lt;p&gt;&lt;a href="https://www.fharrell.com/talk/bthink/"&gt;Talk details from Frank Harrell&amp;rsquo;s blog&lt;/a&gt; - includes slides&lt;/p&gt;
&lt;p&gt;This beautiful talk about Bayesian Thinking by &lt;a href="https://bsky.app/profile/f2harrell.bsky.social"&gt;Frank Harrell&lt;/a&gt; should be essential material for scientists who are trained in frequentist methods. The talk covers the shortcomings of frequentist approaches, but more importantly the paths out of those quagmires are also shown.&lt;/p&gt;
&lt;p&gt;Frank discusses his journey to Bayesian stats in this &lt;a href="https://www.fharrell.com/post/journey/"&gt;blog post from 2017&lt;/a&gt; which is also in the next section.&lt;/p&gt;</description></item></channel></rss>