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typo #479

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typo #479

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2 changes: 1 addition & 1 deletion Statistical_Inference/ConditionalProbability/lesson
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Expand Up @@ -59,7 +59,7 @@
Output: Suppose we don't know P(A) itself, but only know its conditional probabilities, that is, the probability that it occurs if B occurs and the probability that it occurs if B doesn't occur. These are P(A|B) and P(A|~B), respectively. We use ~B to represent 'not B' or 'B complement'.

- Class: text
Output: We can then express P(A) = P(A|B) * P(B) + P(A|~B) * P(~B) and substitute this is into the denominator of Bayes' Formula.
Output: We can then express P(A) = P(A|B) * P(B) + P(A|~B) * P(~B) and substitute this into the denominator of Bayes' Formula.

- Class: text
Output: P(B|A) = P(A|B) * P(B) / ( P(A|B) * P(B) + P(A|~B) * P(~B) )
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