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	<title>Comments on: Rankings: never a bell curve, not always a power law</title>
	<link>http://www.econometa.com/archives/25</link>
	<description>The economy of stuff about stuff</description>
	<pubDate>Fri, 21 Nov 2008 00:48:54 +0000</pubDate>
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		<title>By: admin</title>
		<link>http://www.econometa.com/archives/25#comment-15776</link>
		<author>admin</author>
		<pubDate>Thu, 19 Jul 2007 23:02:52 +0000</pubDate>
		<guid>http://www.econometa.com/archives/25#comment-15776</guid>
		<description>Hi Michael,

Thanks for the comment! You're right, how sharply the tail ends and how peaked it is at the head can completely change the meaning of a ranked histogram. That's why they can be misleading; it's safer to consider the associated PDF instead, if the question you want to answer has to do with averages, etc.</description>
		<content:encoded><![CDATA[<p>Hi Michael,</p>
<p>Thanks for the comment! You&#8217;re right, how sharply the tail ends and how peaked it is at the head can completely change the meaning of a ranked histogram. That&#8217;s why they can be misleading; it&#8217;s safer to consider the associated PDF instead, if the question you want to answer has to do with averages, etc.</p>
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		<title>By: michael webster</title>
		<link>http://www.econometa.com/archives/25#comment-15774</link>
		<author>michael webster</author>
		<pubDate>Tue, 17 Jul 2007 18:47:58 +0000</pubDate>
		<guid>http://www.econometa.com/archives/25#comment-15774</guid>
		<description>I found this discussion very helpful, especially in conjunction with reading Taleb's new book.

The histogram that you derived from a gaussian PDF actually does look like many of the reall histograms -with a sharp ending marking the end of the shelf, lack of any new entries, etc.

Interesting that the difference between a gaussian PDF, the related histogram, and histograms with power law PDF's may just depend upon how sharply the tail comes to an conclusion -or at least that is my conclusion after reading this article.</description>
		<content:encoded><![CDATA[<p>I found this discussion very helpful, especially in conjunction with reading Taleb&#8217;s new book.</p>
<p>The histogram that you derived from a gaussian PDF actually does look like many of the reall histograms -with a sharp ending marking the end of the shelf, lack of any new entries, etc.</p>
<p>Interesting that the difference between a gaussian PDF, the related histogram, and histograms with power law PDF&#8217;s may just depend upon how sharply the tail comes to an conclusion -or at least that is my conclusion after reading this article.</p>
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		<title>By: purple motes &#187; lack of power laws and other popularity problems</title>
		<link>http://www.econometa.com/archives/25#comment-4356</link>
		<author>purple motes &#187; lack of power laws and other popularity problems</author>
		<pubDate>Mon, 21 Aug 2006 23:25:42 +0000</pubDate>
		<guid>http://www.econometa.com/archives/25#comment-4356</guid>
		<description>[...] Power laws and log-normal distributions are two-parameter distributions. The distributional form that best characterizes traffic to all pages may have many more than two parameters. Compared to a log-normal distributions and other distributions with more than two paramters, an approximating line has greater value for providing a simple, intuitive description of an important part of the popularity distribution. [...]</description>
		<content:encoded><![CDATA[<p>[&#8230;] Power laws and log-normal distributions are two-parameter distributions. The distributional form that best characterizes traffic to all pages may have many more than two parameters. Compared to a log-normal distributions and other distributions with more than two paramters, an approximating line has greater value for providing a simple, intuitive description of an important part of the popularity distribution. [&#8230;]</p>
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		<title>By: Adam</title>
		<link>http://www.econometa.com/archives/25#comment-114</link>
		<author>Adam</author>
		<pubDate>Mon, 31 Oct 2005 18:47:21 +0000</pubDate>
		<guid>http://www.econometa.com/archives/25#comment-114</guid>
		<description>Hi Student, 

I'm not sure what you mean about the "general shape" of a CDF. Maybe you mean that a CDF often gives the probability of any outcome less than or equal to x, while I'm showing the probability of any outcome *greater* than or equal to x? If so, this is not an unusual variant, as I mentioned at the very end of &lt;a href="http://www.econometa.com/archives/15" rel="nofollow"&gt;this post&lt;/a&gt;; for example, a Pareto distribution is this latter type of CDF.

Adam</description>
		<content:encoded><![CDATA[<p>Hi Student, </p>
<p>I&#8217;m not sure what you mean about the &#8220;general shape&#8221; of a CDF. Maybe you mean that a CDF often gives the probability of any outcome less than or equal to x, while I&#8217;m showing the probability of any outcome *greater* than or equal to x? If so, this is not an unusual variant, as I mentioned at the very end of <a href="http://www.econometa.com/archives/15" rel="nofollow">this post</a>; for example, a Pareto distribution is this latter type of CDF.</p>
<p>Adam</p>
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	<item>
		<title>By: Student</title>
		<link>http://www.econometa.com/archives/25#comment-111</link>
		<author>Student</author>
		<pubDate>Sun, 30 Oct 2005 19:42:28 +0000</pubDate>
		<guid>http://www.econometa.com/archives/25#comment-111</guid>
		<description>Dear poster,

Please revise on the general shape of a CDF before posting graphs.  It will make your point palatable beyond the statistically illiterate.

Cheers,

Student</description>
		<content:encoded><![CDATA[<p>Dear poster,</p>
<p>Please revise on the general shape of a CDF before posting graphs.  It will make your point palatable beyond the statistically illiterate.</p>
<p>Cheers,</p>
<p>Student</p>
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