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	<title>
	Comments on: An Intuitive (and Short) Explanation of Bayes&#8217; Theorem	</title>
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	<link>https://betterexplained.com/articles/an-intuitive-and-short-explanation-of-bayes-theorem/</link>
	<description>Math lessons that click</description>
	<lastBuildDate>Tue, 06 Oct 2026 00:52:43 +0000</lastBuildDate>
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		<title>
		By: Josh		</title>
		<link>https://betterexplained.com/articles/an-intuitive-and-short-explanation-of-bayes-theorem/#comment-568437</link>

		<dc:creator><![CDATA[Josh]]></dc:creator>
		<pubDate>Tue, 06 Oct 2026 00:52:43 +0000</pubDate>
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					<description><![CDATA[&lt;p&gt;In actuality I have cancer or i dont, and probabilities are just estimates based on the available information. How do you account for information that you have, that the scientists evaluating the cancer test don&#039;t have? &lt;br&gt;Using the available information, a positive test means theres a 7.8% chance i have cancer, but this is based on me being a random member of the public given a test. This doesn&#039;t account for the fact that I have, for example, a weird mark on my skin.&lt;/p&gt;&lt;p&gt;If we know the chances of the test giving false and negative results based on either having or not having cancer, then can we use that in combination with the probability of, for example, a weird mark being caused by cancer or something else?&lt;/p&gt;&lt;p&gt;I looked at a study ( &lt;a href=&quot;https://doi.org/10.1155/2021/6618990&quot; title=&quot;https://doi.org/10.1155/2021/6618990&quot; rel=&quot;nofollow ugc&quot;&gt;https://doi.org/10.1155/2021/6618990&lt;/a&gt; ) that said 90.48% of the doctors in their tests were correct when they identified a mark as cancerous. If my doctor has said my mark looks like cancer, is it logically sound to use this value as my hypothesis and calculate a 98.75% of me having cancer given a positive test?&lt;/p&gt;]]></description>
			<content:encoded><![CDATA[<p>In actuality I have cancer or i dont, and probabilities are just estimates based on the available information. How do you account for information that you have, that the scientists evaluating the cancer test don&#8217;t have? <br />Using the available information, a positive test means theres a 7.8% chance i have cancer, but this is based on me being a random member of the public given a test. This doesn&#8217;t account for the fact that I have, for example, a weird mark on my skin.</p>
<p>If we know the chances of the test giving false and negative results based on either having or not having cancer, then can we use that in combination with the probability of, for example, a weird mark being caused by cancer or something else?</p>
<p>I looked at a study ( <a href="https://doi.org/10.1155/2021/6618990" title="https://doi.org/10.1155/2021/6618990" rel="nofollow ugc">https://doi.org/10.1155/2021/6618990</a> ) that said 90.48% of the doctors in their tests were correct when they identified a mark as cancerous. If my doctor has said my mark looks like cancer, is it logically sound to use this value as my hypothesis and calculate a 98.75% of me having cancer given a positive test?</p>
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		<item>
		<title>
		By: Supreme Potato		</title>
		<link>https://betterexplained.com/articles/an-intuitive-and-short-explanation-of-bayes-theorem/#comment-568412</link>

		<dc:creator><![CDATA[Supreme Potato]]></dc:creator>
		<pubDate>Wed, 25 Mar 2026 02:57:11 +0000</pubDate>
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					<description><![CDATA[&lt;p&gt;Dude, your phrasing of Bayes Theorem is awesome. Tysm&lt;/p&gt;]]></description>
			<content:encoded><![CDATA[<p>Dude, your phrasing of Bayes Theorem is awesome. Tysm</p>
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		<item>
		<title>
		By: Claude Courty		</title>
		<link>https://betterexplained.com/articles/an-intuitive-and-short-explanation-of-bayes-theorem/#comment-568405</link>

		<dc:creator><![CDATA[Claude Courty]]></dc:creator>
		<pubDate>Sat, 14 Feb 2026 15:29:42 +0000</pubDate>
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					<description><![CDATA[&lt;p&gt;... Sans compter les approximations d&#039;ordre sémantique du présent document, se voulant démonstratif : confusion entre chance, risque et probabilité.&lt;/p&gt;]]></description>
			<content:encoded><![CDATA[<p>&#8230; Sans compter les approximations d&#8217;ordre sémantique du présent document, se voulant démonstratif : confusion entre chance, risque et probabilité.</p>
]]></content:encoded>
		
			</item>
		<item>
		<title>
		By: Claude Courty		</title>
		<link>https://betterexplained.com/articles/an-intuitive-and-short-explanation-of-bayes-theorem/#comment-568404</link>

		<dc:creator><![CDATA[Claude Courty]]></dc:creator>
		<pubDate>Sat, 14 Feb 2026 15:26:35 +0000</pubDate>
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					<description><![CDATA[&lt;p&gt;Ne pouvant prétendre à la logique expérimentale (cf. Pareto) ou même simplement déductive, puisque reposant sur des probabilités, le filtrage bayésien ne peut offrir que des compromis, et perd de ce fait, par définition, toute valeur de test.&lt;/p&gt;]]></description>
			<content:encoded><![CDATA[<p>Ne pouvant prétendre à la logique expérimentale (cf. Pareto) ou même simplement déductive, puisque reposant sur des probabilités, le filtrage bayésien ne peut offrir que des compromis, et perd de ce fait, par définition, toute valeur de test.</p>
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