Finished the notes
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</introduction>
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<subsection xml:id="subsec-hw1-review">
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<title>HW 1 Q5</title>
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<p>
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Write <m>F</m> for the event that there's a fire and <m>S</m> for the event that there's visible smoke.
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Then the information we're given can be interpreted as:
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<md>
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<mrow> \Pr(F) \amp = 0.01 </mrow>
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<mrow> \Pr(S) \amp = 0.1 </mrow>
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<mrow> \Pr(S\mid F) \amp = 0.9 </mrow>
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</md>
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In this case, we can use the simpler version of Bayes' Theorem:
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<md>
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<mrow> \Pr(F \mid S) = \frac{\Pr(S \mid F)\Pr(F)}{\Pr(S)} = \dotsb </mrow>
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</md>
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Unlike our usual diagnostic testing examples, we do have access to the denominator probability here.
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</p>
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</subsection>
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<subsection xml:id="subsec-Discrete-Random-Variables">
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<title>Sec 2.1: Random Variables</title>
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