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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>independence: Fast Rank Tests · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2010.09712/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:16:22 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/2010.09712/feed.xml" rel="self" type="application/rss+xml" /><item><title>independence: Fast Rank Tests — mentioned by CrazyStat</title><link>https://news.ycombinator.com/item?id=39462454</link><guid isPermaLink="false">urn:hackerpapers:mention:2010.09712:39462454</guid><pubDate>Thu, 22 Feb 2024 02:32:30 GMT</pubDate><description>&lt;p&gt;&amp;gt; The final computation of Hoeffding&amp;#x27;s D involves a formula that normalizes this sum, taking into account the total number of data points and the expected values under the assumption of independence. The result is a measure that ranges from -0.5 to 1, where values near 0 indicate no association, values closer to 1 indicate a strong positive association, and values near -0.5 suggest a strong negative association. This is incorrect. Hoeffding&amp;#x27;s D was not intended to be used as a descriptive statistic to measure the strength or direction of a relationship, it&amp;#x27;s just a statistic from a…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2010.09712/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>stat.CO</category></item></channel></rss>
