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	<title>Some stuff &#187; Probability</title>
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		<title>die throwing problem</title>
		<link>https://blog.yhuang.org/?p=1796</link>
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		<pubDate>Thu, 14 Sep 2017 03:21:41 +0000</pubDate>
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		<category><![CDATA[dice]]></category>
		<category><![CDATA[math]]></category>
		<category><![CDATA[Probability]]></category>
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		<guid isPermaLink="false">http://scripts.mit.edu/~zong/wpress/?p=1796</guid>
		<description><![CDATA[Here&#8217;s a link to a subtle probability problem. You throw a die until you get 6. What is the expected number of throws (including the throw giving 6) conditioned on the event that all throws gave even numbers? The &#8220;obvious&#8221; answer is incorrect. The correct answer can be brute-forced by computing probabilities of this sort: [...]]]></description>
			<content:encoded><![CDATA[<p>Here&#8217;s a <a href="https://gilkalai.wordpress.com/2017/09/08/elchanan-mossels-amazing-dice-paradox-answers-to-tyi-30/">link</a> to a subtle probability problem.</p>
<blockquote><p>You throw a die until you get 6. What is the expected number of throws (including the throw giving 6) conditioned on the event that all throws gave even numbers?</p></blockquote>
<p>The &#8220;obvious&#8221; answer is incorrect.<br />
<span id="more-1796"></span><br />
The correct answer can be brute-forced by computing probabilities of this sort:<br />
If \(s\) is a sequence of length \(n\), then<br />
\(P_n\triangleq\) = P(\(s\) ends in 6 and \(s\) all even) = \((2/6)^{n-1} (1/6)\)<br />
(The total probability over all \(n\) is therefore \(Z=(1/6)/(4/6)=1/4\).)<br />
The expected length of \(s\) is \(\sum_{n=1}^\infty n (P_n / Z)\)<br />
\(= \sum_{n=1}^\infty n (2/6)^{n-1} (1/6) / (1/4) = \sum_{n=1}^\infty n (2/6)^{n-1} (2/3) = 3/2\)</p>
<p>This is interesting since premature conditioning on the 3 even sides of a die in every roll produces an (incorrect) expected length of 3.</p>
<p>There is already an elegant and convincing derivation of the correct answer attributed to Paul Cuff if you follow the links from the original article, but here&#8217;s an intuitive explanation for why the <em>incorrect</em> answer overestimates the expected length in such a way &#8211;</p>
<p>Notice that in \(P_n\) the probability \((1/6)\) of obtaining the final 6 has no effect on the expected length. The expected length depends entirely on the shape of \(P_n\) over \(n\). The calculation for the &#8220;incorrect&#8221; reasoning would have made the sum \(\sum_{n=1}^\infty n (2/3)^{n-1} (1/3) = 3\), and the difference is in the \((2/3)^{n-1}\) vs. \((2/6)^{n-1}\) term. So the existence of 1, 3, and 5 matter; they make longer prefixes of 2 and 4 even less likely, as more of the longer sequences that would have been valid ends up containing a 1, 3, or 5 instead and getting thrown away.</p>
<p>Note: There is also a good discussion <a href="https://www.quora.com/What-is-the-expected-number-of-rolls-of-a-fair-six-sided-die-to-get-a-6-given-that-all-rolls-leading-up-to-that-6-are-even-numbered">on Quora</a>.</p>
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