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Conditional probability

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Summary

For events AA and BB with P(B)>0\mathbb P(B)>0, the normalized probability P(A∣B)=P(A∩B)/P(B)\mathbb P(A\mid B)=\mathbb P(A\cap B)/\mathbb P(B).

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Carrier(s)

Data

Axioms / constraints

Canonically induces

Notes

Conditioning on sigma-algebras or null events requires conditional expectation or regular conditional probabilities; the elementary event formula does not cover those cases.

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Probability spaceConditional probability

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Authored explanation

For an event BB with P(B)>0\mathbb P(B)>0, restricting P\mathbb P to intersections with BB and dividing by P(B)\mathbb P(B) gives the conditional probability measure.

How to interpret this relation type

Apply a standard functorial or canonical construction whose output is not merely a reduct of the input and is not generally an equivalent presentation of the same object.

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