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    <title>P-Value on Md Ahsanul Islam</title>
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      <title>Significant and Not Significant Are Not Significantly Different</title>
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      <pubDate>Sun, 11 Oct 2026 00:00:00 +0000</pubDate>
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      <description>&lt;p&gt;A training program improves test scores for men (&lt;code&gt;\(p = 0.009\)&lt;/code&gt;) but not for women (&lt;code&gt;\(p = 0.23\)&lt;/code&gt;). A drug lowers blood pressure in one trial and “fails” in another. In a regression, TV advertising predicts sales but radio advertising does not. Each of these sentences invites the same conclusion, which is, the two things behave differently.&lt;/p&gt;&#xA;&lt;p&gt;That conclusion does not follow. It is one of the most common errors in applied statistics, and Gelman and Stern (&lt;a href=&#34;#ref-gelman2006&#34;&gt;2006&lt;/a&gt;) gave it a memorable name in &lt;em&gt;The American Statistician&lt;/em&gt;: &lt;strong&gt;the difference between “significant” and “not significant” is not itself statistically significant&lt;/strong&gt;. A free copy of the paper is on &lt;a href=&#34;https://sites.stat.columbia.edu/gelman/research/published/signif4.pdf&#34;&gt;Andrew Gelman’s website&lt;/a&gt;.&lt;/p&gt;</description>
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