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	<title>Comments on: Think Frequencies, Not Probabilities</title>
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	<link>http://www.overcomingbias.com/2007/02/think_frequenci.html</link>
	<description>Overcoming Bias is economist Robin Hanson’s blog, on honesty, signaling, disagreement, forecasting, and the far future.</description>
	<lastBuildDate>Sat, 11 Feb 2012 23:23:58 +0000</lastBuildDate>
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		<title>By: Eliezer Yudkowsky</title>
		<link>http://www.overcomingbias.com/2007/02/think_frequenci.html#comment-421721</link>
		<dc:creator>Eliezer Yudkowsky</dc:creator>
		<pubDate>Sun, 25 Feb 2007 01:41:40 +0000</pubDate>
		<guid isPermaLink="false">http://prod.ob.trike.com.au/2007/02/think-frequencies-not-probabilities.html#comment-421721</guid>
		<description>Self-plug: Anyone who has trouble teaching Bayes&#039;s Theorem to high school students can send them to &lt;a href=&quot;http://yudkowsky.net/bayes/bayes.html&quot; rel=&quot;nofollow&quot;&gt;An Intuitive Explanation of Bayesian Reasoning&lt;/a&gt;, which I designed after reading all the pessimistic papers about how hard it is to get subjects to retain Bayes&#039;s Theorem for two weeks.  Includes neat Java applets.
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		<content:encoded><![CDATA[<p>Self-plug: Anyone who has trouble teaching Bayes&#8217;s Theorem to high school students can send them to <a href="http://yudkowsky.net/bayes/bayes.html" rel="nofollow">An Intuitive Explanation of Bayesian Reasoning</a>, which I designed after reading all the pessimistic papers about how hard it is to get subjects to retain Bayes&#8217;s Theorem for two weeks.  Includes neat Java applets.</p>
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		<title>By: Arnold Kling</title>
		<link>http://www.overcomingbias.com/2007/02/think_frequenci.html#comment-421720</link>
		<dc:creator>Arnold Kling</dc:creator>
		<pubDate>Sat, 24 Feb 2007 23:35:05 +0000</pubDate>
		<guid isPermaLink="false">http://prod.ob.trike.com.au/2007/02/think-frequencies-not-probabilities.html#comment-421720</guid>
		<description>In teaching AP statistics in high school, I have found that many students have an easier time doing a conditional probability or Bayes&#039; Theorem problem if they put everything in terms of a total frequency of 100.

I think that this has something to do with preferring concrete to abstract, but I&#039;m not sure.
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		<content:encoded><![CDATA[<p>In teaching AP statistics in high school, I have found that many students have an easier time doing a conditional probability or Bayes&#8217; Theorem problem if they put everything in terms of a total frequency of 100.</p>
<p>I think that this has something to do with preferring concrete to abstract, but I&#8217;m not sure.</p>
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		<title>By: Roy</title>
		<link>http://www.overcomingbias.com/2007/02/think_frequenci.html#comment-421719</link>
		<dc:creator>Roy</dc:creator>
		<pubDate>Fri, 23 Feb 2007 16:43:53 +0000</pubDate>
		<guid isPermaLink="false">http://prod.ob.trike.com.au/2007/02/think-frequencies-not-probabilities.html#comment-421719</guid>
		<description>Is the issue really visualization of probabilities or the fact that conditional probabilities are tricky to interpret because they deemphasize the a priori probabilities? To me, both desriptions are confusing. Why not just work with the probabilities of sample outcomes, scaled by an appropriately large group. For this example, why not say &quot;In a thousand tests, we expect that 8 women will test positive and have cancer, 95 women will test positive but not have cancer, 2 women will test negative but actually have cancer and about 895 women will test negative and not have cancer.

This says that a women who test positive can look at the facts and deduce that she is among a group of about 103 who tested positive and about 8 of those women will be found to have cancer, which will suggest the right answer of about 8/103.



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		<content:encoded><![CDATA[<p>Is the issue really visualization of probabilities or the fact that conditional probabilities are tricky to interpret because they deemphasize the a priori probabilities? To me, both desriptions are confusing. Why not just work with the probabilities of sample outcomes, scaled by an appropriately large group. For this example, why not say &#8220;In a thousand tests, we expect that 8 women will test positive and have cancer, 95 women will test positive but not have cancer, 2 women will test negative but actually have cancer and about 895 women will test negative and not have cancer.</p>
<p>This says that a women who test positive can look at the facts and deduce that she is among a group of about 103 who tested positive and about 8 of those women will be found to have cancer, which will suggest the right answer of about 8/103.</p>
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		<title>By: Douglas Knight</title>
		<link>http://www.overcomingbias.com/2007/02/think_frequenci.html#comment-421718</link>
		<dc:creator>Douglas Knight</dc:creator>
		<pubDate>Fri, 23 Feb 2007 15:52:27 +0000</pubDate>
		<guid isPermaLink="false">http://prod.ob.trike.com.au/2007/02/think-frequencies-not-probabilities.html#comment-421718</guid>
		<description>&lt;em&gt;prefer to reason in terms of frequencies&lt;/em&gt;

Do you really mean that as an imperative?
I suspect this is not a matter of bad reasoning, but lack of reasoning. Thus I think that someone willing to put in as much effort as to rephrase the problem, was going to solve it anyhow.

Thus, I think a more helpful heuristic would be to make other people encounter frequencies, rather than probabilities. But this is a pretty contrived example: surely it would be better to give the doctor false positive rates than to make it easier for the doctor to compute them.
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		<content:encoded><![CDATA[<p><em>prefer to reason in terms of frequencies</em></p>
<p>Do you really mean that as an imperative?<br />
I suspect this is not a matter of bad reasoning, but lack of reasoning. Thus I think that someone willing to put in as much effort as to rephrase the problem, was going to solve it anyhow.</p>
<p>Thus, I think a more helpful heuristic would be to make other people encounter frequencies, rather than probabilities. But this is a pretty contrived example: surely it would be better to give the doctor false positive rates than to make it easier for the doctor to compute them.</p>
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		<title>By: Anders Sandberg</title>
		<link>http://www.overcomingbias.com/2007/02/think_frequenci.html#comment-421717</link>
		<dc:creator>Anders Sandberg</dc:creator>
		<pubDate>Fri, 23 Feb 2007 12:23:31 +0000</pubDate>
		<guid isPermaLink="false">http://prod.ob.trike.com.au/2007/02/think-frequencies-not-probabilities.html#comment-421717</guid>
		<description>This is why visualising risks of different options using dartboards and roulette wheels likely works so well, while pie charts (more based on frequency) do badly. See Hoffman JR, Wilkes MS, Day FC, Bell DS, Higa JK (2006) The Roulette Wheel: An Aid to Informed Decision Making. PLoS Med 3(6): e137 doi:10.1371/journal.pmed.0030137

Still, people tend to estimate areas as the real area to the power of 0.7, http://en.wikipedia.org/wiki/Stevens%27_power_law and this might still give an overestimation of small areas compared to large ones.
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		<content:encoded><![CDATA[<p>This is why visualising risks of different options using dartboards and roulette wheels likely works so well, while pie charts (more based on frequency) do badly. See Hoffman JR, Wilkes MS, Day FC, Bell DS, Higa JK (2006) The Roulette Wheel: An Aid to Informed Decision Making. PLoS Med 3(6): e137 doi:10.1371/journal.pmed.0030137</p>
<p>Still, people tend to estimate areas as the real area to the power of 0.7, <a href="http://en.wikipedia.org/wiki/Stevens%27_power_law" rel="nofollow">http://en.wikipedia.org/wiki/Stevens%27_power_law</a> and this might still give an overestimation of small areas compared to large ones.</p>
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