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	<title>Comments on: Understanding the Birthday Paradox</title>
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	<link>http://betterexplained.com/articles/understanding-the-birthday-paradox/</link>
	<description>Learning shouldn't hurt. Let's share the insights that made difficult ideas click.</description>
	<lastBuildDate>Fri, 20 Nov 2009 14:09:06 -0800</lastBuildDate>
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		<title>By: Roy</title>
		<link>http://betterexplained.com/articles/understanding-the-birthday-paradox/#comment-252549</link>
		<dc:creator>Roy</dc:creator>
		<pubDate>Sun, 13 Sep 2009 19:20:00 +0000</pubDate>
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		<description>Aren&#039;t there 366 possible birthdays? (feb 29)</description>
		<content:encoded><![CDATA[<p>Aren&#8217;t there 366 possible birthdays? (feb 29)</p>
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		<title>By: Sean</title>
		<link>http://betterexplained.com/articles/understanding-the-birthday-paradox/#comment-252341</link>
		<dc:creator>Sean</dc:creator>
		<pubDate>Fri, 11 Sep 2009 20:06:34 +0000</pubDate>
		<guid isPermaLink="false">http://betterexplained.com/articles/understanding-the-birthday-paradox/#comment-252341</guid>
		<description>The explanations given are all approximations, in order to get an exact result you follow the start to Appendix A, but don&#039;t attempt to simplify with e^x.  The solution is actually fairly simple, for n possibilities (days in the year) and k events (people at the party) we get a probability of:

1 - (P(n-1,k-1)/(n^(k-1))).
Where P(n,k) is the number of ways to pick k elements from a set of n, or n!/(n-k)!.

This will give an exact solution, the probability of finding two people with the same birthday from a crowd of 23 is more accurately: 50.7297234%

I hope that this makes sense, if it doesn&#039;t, look at the page on combinatorics and/or think about the fact that (1-(j/n)) = ((n-j)/n) with reference to Appendix A.</description>
		<content:encoded><![CDATA[<p>The explanations given are all approximations, in order to get an exact result you follow the start to Appendix A, but don&#8217;t attempt to simplify with e^x.  The solution is actually fairly simple, for n possibilities (days in the year) and k events (people at the party) we get a probability of:</p>
<p>1 &#8211; (P(n-1,k-1)/(n^(k-1))).<br />
Where P(n,k) is the number of ways to pick k elements from a set of n, or n!/(n-k)!.</p>
<p>This will give an exact solution, the probability of finding two people with the same birthday from a crowd of 23 is more accurately: 50.7297234%</p>
<p>I hope that this makes sense, if it doesn&#8217;t, look at the page on combinatorics and/or think about the fact that (1-(j/n)) = ((n-j)/n) with reference to Appendix A.</p>
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		<title>By: The Birthday Paradox &#124; by Jeremia Froyland</title>
		<link>http://betterexplained.com/articles/understanding-the-birthday-paradox/#comment-249442</link>
		<dc:creator>The Birthday Paradox &#124; by Jeremia Froyland</dc:creator>
		<pubDate>Sat, 01 Aug 2009 20:13:10 +0000</pubDate>
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		<description>[...] The math gets somewhat complicated, but you can check it out in more detail: Understanding the Birthday Paradox and Wikipedia&#8217;s page. [...]</description>
		<content:encoded><![CDATA[<p>[...] The math gets somewhat complicated, but you can check it out in more detail: Understanding the Birthday Paradox and Wikipedia&#8217;s page. [...]</p>
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