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	<id>https://www.rasmusen.org/rasmapedia/index.php?action=history&amp;feed=atom&amp;title=Outliers</id>
	<title>Outliers - Revision history</title>
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	<updated>2026-05-05T23:16:47Z</updated>
	<subtitle>Revision history for this page on the wiki</subtitle>
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	<entry>
		<id>https://www.rasmusen.org/rasmapedia/index.php?title=Outliers&amp;diff=3175&amp;oldid=prev</id>
		<title>Rasmusen p1vaim at 16:40, 25 May 2021</title>
		<link rel="alternate" type="text/html" href="https://www.rasmusen.org/rasmapedia/index.php?title=Outliers&amp;diff=3175&amp;oldid=prev"/>
		<updated>2021-05-25T16:40:15Z</updated>

		<summary type="html">&lt;p&gt;&lt;/p&gt;
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				&lt;td colspan=&quot;2&quot; style=&quot;background-color: #fff; color: #222; text-align: center;&quot;&gt;← Older revision&lt;/td&gt;
				&lt;td colspan=&quot;2&quot; style=&quot;background-color: #fff; color: #222; text-align: center;&quot;&gt;Revision as of 16:40, 25 May 2021&lt;/td&gt;
				&lt;/tr&gt;&lt;tr&gt;&lt;td colspan=&quot;2&quot; class=&quot;diff-lineno&quot; id=&quot;mw-diff-left-l1&quot; &gt;Line 1:&lt;/td&gt;
&lt;td colspan=&quot;2&quot; class=&quot;diff-lineno&quot;&gt;Line 1:&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt;−&lt;/td&gt;&lt;td style=&quot;color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&lt;del class=&quot;diffchange diffchange-inline&quot;&gt; &lt;/del&gt;Suppose you have two observations, $y_1 =70$ and $y_2 = 100$, where  $y_i = \mu + \epsilon$ with which to estimate the value of $\mu$, with $\epsilon_1 \tilde N(0,10)$ and  &lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt;+&lt;/td&gt;&lt;td style=&quot;color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;Suppose you have two observations, $y_1 =70$ and $y_2 = 100$, where  $y_i = \mu + \epsilon$ with which to estimate the value of $\mu$, with $\epsilon_1 \tilde N(0,10)$ and  &lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;$\epsilon_2\tilde \{(.5, -40), (.5, +40)\}$. What should our estimate $\hat{\mu}$ be?  &lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;$\epsilon_2\tilde \{(.5, -40), (.5, +40)\}$. What should our estimate $\hat{\mu}$ be?  &lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt;−&lt;/td&gt;&lt;td style=&quot;color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&lt;del class=&quot;diffchange diffchange-inline&quot;&gt; &lt;/del&gt;This would make a good note. American Mathematical Monthly. Get a loss function-- probably any convex loss function is OK, but start with quadratic. The answer must be something like 104.  The point is: don't discard outliers, but think about what htey mean.  &lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt;+&lt;/td&gt;&lt;td style=&quot;color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;This would make a good note. American Mathematical Monthly. Get a loss function-- probably any convex loss function is OK, but start with quadratic. The answer must be something like 104.  The point is: don't discard outliers, but think about what htey mean&lt;ins class=&quot;diffchange diffchange-inline&quot;&gt;. &lt;/ins&gt;&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td colspan=&quot;2&quot;&gt; &lt;/td&gt;&lt;td class='diff-marker'&gt;+&lt;/td&gt;&lt;td style=&quot;color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt; &lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td colspan=&quot;2&quot;&gt; &lt;/td&gt;&lt;td class='diff-marker'&gt;+&lt;/td&gt;&lt;td style=&quot;color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;&lt;ins class=&quot;diffchange diffchange-inline&quot;&gt; I need to get the Math extension to work in Mediawiki. I have it in localsettings, so i just need it to update&lt;/ins&gt;.  &lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;tr&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;----&lt;/div&gt;&lt;/td&gt;&lt;td class='diff-marker'&gt; &lt;/td&gt;&lt;td style=&quot;background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;&quot;&gt;&lt;div&gt;----&lt;/div&gt;&lt;/td&gt;&lt;/tr&gt;
&lt;/table&gt;</summary>
		<author><name>Rasmusen p1vaim</name></author>
		
	</entry>
	<entry>
		<id>https://www.rasmusen.org/rasmapedia/index.php?title=Outliers&amp;diff=3174&amp;oldid=prev</id>
		<title>Rasmusen p1vaim: Created page with &quot; Suppose you have two observations, $y_1 =70$ and $y_2 = 100$, where  $y_i = \mu + \epsilon$ with which to estimate the value of $\mu$, with $\epsilon_1 \tilde N(0,10)$ and  $...&quot;</title>
		<link rel="alternate" type="text/html" href="https://www.rasmusen.org/rasmapedia/index.php?title=Outliers&amp;diff=3174&amp;oldid=prev"/>
		<updated>2021-05-25T16:39:27Z</updated>

		<summary type="html">&lt;p&gt;Created page with &amp;quot; Suppose you have two observations, $y_1 =70$ and $y_2 = 100$, where  $y_i = \mu + \epsilon$ with which to estimate the value of $\mu$, with $\epsilon_1 \tilde N(0,10)$ and  $...&amp;quot;&lt;/p&gt;
&lt;p&gt;&lt;b&gt;New page&lt;/b&gt;&lt;/p&gt;&lt;div&gt; Suppose you have two observations, $y_1 =70$ and $y_2 = 100$, where  $y_i = \mu + \epsilon$ with which to estimate the value of $\mu$, with $\epsilon_1 \tilde N(0,10)$ and &lt;br /&gt;
$\epsilon_2\tilde \{(.5, -40), (.5, +40)\}$. What should our estimate $\hat{\mu}$ be? &lt;br /&gt;
&lt;br /&gt;
 This would make a good note. American Mathematical Monthly. Get a loss function-- probably any convex loss function is OK, but start with quadratic. The answer must be something like 104.  The point is: don't discard outliers, but think about what htey mean. &lt;br /&gt;
&lt;br /&gt;
----&lt;/div&gt;</summary>
		<author><name>Rasmusen p1vaim</name></author>
		
	</entry>
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