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	<title>The Shape of Code &#187; academics</title>
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		<title>A power law artifact</title>
		<link>http://shape-of-code.coding-guidelines.com/2008/12/03/a-power-law-artifact/</link>
		<comments>http://shape-of-code.coding-guidelines.com/2008/12/03/a-power-law-artifact/#comments</comments>
		<pubDate>Wed, 03 Dec 2008 23:44:29 +0000</pubDate>
		<dc:creator>Derek-Jones</dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[academics]]></category>
		<category><![CDATA[cognitive psychology]]></category>
		<category><![CDATA[power-law]]></category>

		<guid isPermaLink="false">http://shape-of-code.coding-guidelines.com/?p=16</guid>
		<description><![CDATA[Over the last few years software engineering academics have jumped aboard the power-law band-wagon (examples here and here). With few exceptions (one here) these researchers have done little more that plot their data on a log-log graph and shown that a straight line is a good fit for many of the points. What a sorry [...]]]></description>
			<content:encoded><![CDATA[<p>Over the last few years software engineering academics have jumped aboard the <a href="http://en.wikipedia.org/wiki/Power_law">power-law</a> band-wagon (examples <a href="http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.114.182">here</a> and <a href="http://www.dmst.aueb.gr/dds/pubs/jrnl/2008-TOSEM-PowerLaws/html/LSV08.pdf">here</a>).  With few exceptions (one <a href="http://homepages.mcs.vuw.ac.nz/~marcus/manuscripts/BaxterShape.pdf">here</a>) these researchers have done little more that plot their data on a log-log graph and shown that a straight line is a good fit for many of the points.  What a sorry state of affairs.</p>
<p><a href="http://en.wikipedia.org/wiki/Cognitive_psychology">Cognitive psychologists</a> have also encountered straight lines in log-log graphs, but they have been in the analysis of data business much longer and are aware that there might be <a href="http://en.wikipedia.org/wiki/Exponential_distribution">other distributions</a> that are just as straight in the same places.</p>
<p>A very interesting paper, <a href="http://www.psy.ucsd.edu/~dhuber/math_readings/Myung_Kim_Pitt_2000.pdf">Toward an explanation of the power law artifact: Insights from response surface analysis</a>, shows how averaging data obtained from a variety of sources (example given is the performance of different subjects in a psychology experiment) can produce a power law where none originally existed.  The underlying fault could be that data from a <a href="http://en.wikipedia.org/wiki/Non-linear">non-linear</a> system is being averaged using the <a href="http://en.wikipedia.org/wiki/Arithmetic_mean">arithmetic mean</a> (I suspect that I have done this in the past), which it turns out should only be used to average data from a linear system.  The authors list the appropriate averaging formula that should be used for various non-linear systems.</p>
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