<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Sample Variance on gdpark.blog</title><link>https://gdpark.blog/tags/sample-variance/</link><description>Recent content in Sample Variance on gdpark.blog</description><generator>Hugo</generator><language>en</language><lastBuildDate>Fri, 17 Nov 2017 00:00:00 +0000</lastBuildDate><atom:link href="https://gdpark.blog/tags/sample-variance/index.xml" rel="self" type="application/rss+xml"/><item><title>Introduction [Basic Statistics I Studied #1]</title><link>https://gdpark.blog/posts/statistics-01-introduction/</link><pubDate>Sun, 12 Nov 2017 00:00:00 +0000</pubDate><guid>https://gdpark.blog/posts/statistics-01-introduction/</guid><description>A casual dive into why sample variance divides by n-1 and how we use samples to estimate population parameters without measuring absolutely everyone.</description></item><item><title>Derivation of the Chi-Squared Distribution [Basic Statistics I Studied #5]</title><link>https://gdpark.blog/posts/statistics-05-derivation-of-the-chi-squared-distribution/</link><pubDate>Fri, 17 Nov 2017 00:00:00 +0000</pubDate><guid>https://gdpark.blog/posts/statistics-05-derivation-of-the-chi-squared-distribution/</guid><description>Chi-squared is just a gamma in disguise — we prove Z² follows it with 1 degree of freedom and show how sample variance ties in before jumping to the t-distribution.</description></item></channel></rss>