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	<title>Comments on: Bad graphs and bad reporting</title>
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	<link>http://www.chrisamiller.com/blog/2009/05/06/bad-graphs-and-bad-reporting/</link>
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		<title>By: Paul Van Slembrouck</title>
		<link>http://www.chrisamiller.com/blog/2009/05/06/bad-graphs-and-bad-reporting/comment-page-1/#comment-814</link>
		<dc:creator>Paul Van Slembrouck</dc:creator>
		<pubDate>Tue, 16 Jun 2009 05:54:32 +0000</pubDate>
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		<description>but what about other fits of the data other than logarithmic?</description>
		<content:encoded><![CDATA[<p>but what about other fits of the data other than logarithmic?</p>
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		<title>By: Paul Van Slembrouck</title>
		<link>http://www.chrisamiller.com/blog/2009/05/06/bad-graphs-and-bad-reporting/comment-page-1/#comment-813</link>
		<dc:creator>Paul Van Slembrouck</dc:creator>
		<pubDate>Tue, 16 Jun 2009 05:52:43 +0000</pubDate>
		<guid isPermaLink="false">http://www.chrisamiller.com/blog/?p=1781#comment-813</guid>
		<description>Good stuff.  

If I recall correctly, I was taught to throw out relationships with R-Squares less than 0.75.  An R-Sq as low as 0.18 might actually be evidence against the bloggers&#039; hypothesis that time spend eating is related to obesity.  If you threw some more variables in the mix, there would likely be others with higher R-Sq and the R-Sq for time could decrease.  

Just by eyeballing the data points, the relationship appears random--not much correlation standing out.  But, that damn gray curve Catherine added to the graph sucks the casual viewers into thinking that the line reliably means something.  

Also, high five for using OpenOffice.Org.  Down with Microsoft..</description>
		<content:encoded><![CDATA[<p>Good stuff.  </p>
<p>If I recall correctly, I was taught to throw out relationships with R-Squares less than 0.75.  An R-Sq as low as 0.18 might actually be evidence against the bloggers&#8217; hypothesis that time spend eating is related to obesity.  If you threw some more variables in the mix, there would likely be others with higher R-Sq and the R-Sq for time could decrease.  </p>
<p>Just by eyeballing the data points, the relationship appears random&#8211;not much correlation standing out.  But, that damn gray curve Catherine added to the graph sucks the casual viewers into thinking that the line reliably means something.  </p>
<p>Also, high five for using OpenOffice.Org.  Down with Microsoft..</p>
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