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	<title>Comments on: Mistakes in Experimental Design and Interpretation</title>
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	<link>http://management.curiouscatblog.net/2007/06/19/mistakes-in-experimental-design-and-interpretation/</link>
	<description>Management Improvement focused on Deming, lean thinking, innovation, customer focus, six sigma, etc.</description>
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		<title>By: Curious Cat Management Blog » Statistical Learning as the Ultimate Agile Development Tool by Peter Norvig</title>
		<link>http://management.curiouscatblog.net/2007/06/19/mistakes-in-experimental-design-and-interpretation/comment-page-1/#comment-34367</link>
		<dc:creator>Curious Cat Management Blog » Statistical Learning as the Ultimate Agile Development Tool by Peter Norvig</dc:creator>
		<pubDate>Thu, 05 Nov 2009 14:13:36 +0000</pubDate>
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		<description>He looks at the advantages of machine learning versus hand programming every case (for example spelling correction)...</description>
		<content:encoded><![CDATA[<p>He looks at the advantages of machine learning versus hand programming every case (for example spelling correction)&#8230;</p>
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		<title>By: CuriousCat: Data Can't Lie</title>
		<link>http://management.curiouscatblog.net/2007/06/19/mistakes-in-experimental-design-and-interpretation/comment-page-1/#comment-28401</link>
		<dc:creator>CuriousCat: Data Can't Lie</dc:creator>
		<pubDate>Thu, 09 Aug 2007 14:08:45 +0000</pubDate>
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		<description>Many people don’t understand the difference between being manipulated because they can’t understand what the data really says and data itself “lying” (which, of course, doesn’t even make sense). The same confusion can come in when someone just draws the wrong conclusion from the data that exists (and them blames the data for “lying” instead of themselves for drawing a faulty conclusion).</description>
		<content:encoded><![CDATA[<p>Many people don’t understand the difference between being manipulated because they can’t understand what the data really says and data itself “lying” (which, of course, doesn’t even make sense). The same confusion can come in when someone just draws the wrong conclusion from the data that exists (and them blames the data for “lying” instead of themselves for drawing a faulty conclusion).</p>
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