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    <title>Statistics on Nalar</title>
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    <description>Recent content in Statistics on Nalar</description>
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      <title>Bootstrap Confidence Intervals with Resampling</title>
      <link>https://nalar.dev/bootstrap-confidence-intervals-with-resampling/</link>
      <pubDate>Wed, 02 Sep 2026 00:00:00 +0700</pubDate>
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      <description>&lt;p&gt;A point estimate hides uncertainty. Reporting that median latency is 180 ms or a conversion-rate difference is 1.4 percentage points does not show how much that estimate might move if another sample were collected.&lt;/p&gt;&#xA;&lt;p&gt;Bootstrap resampling is a practical way to estimate sampling uncertainty when deriving an analytic formula is difficult or when the statistic is not a simple mean.&lt;/p&gt;&#xA;&lt;h2 id=&#34;the-bootstrap-idea&#34;&gt;The bootstrap idea&lt;/h2&gt;&#xA;&lt;p&gt;Given an observed sample of size &lt;code&gt;n&lt;/code&gt;:&lt;/p&gt;</description>
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      <title>Robust Outlier Detection with Median Absolute Deviation</title>
      <link>https://nalar.dev/robust-outlier-detection-with-median-absolute-deviation/</link>
      <pubDate>Wed, 02 Sep 2026 00:00:00 +0700</pubDate>
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      <description>&lt;p&gt;Outlier detection often begins with a rule such as &amp;ldquo;flag values more than three standard deviations from the mean.&amp;rdquo; That works reasonably well for approximately normal data without severe contamination, but the same extreme observations you want to detect can move both the mean and the standard deviation.&lt;/p&gt;&#xA;&lt;p&gt;Median absolute deviation, usually abbreviated MAD, provides a more robust alternative.&lt;/p&gt;&#xA;&lt;h2 id=&#34;why-mean-and-standard-deviation-can-be-fragile&#34;&gt;Why mean and standard deviation can be fragile&lt;/h2&gt;&#xA;&lt;p&gt;Consider response times in milliseconds:&lt;/p&gt;</description>
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