Math 2.0

statement corollary

Law of total probability for an event and its complement

Statement

Let (Ω,F,P)(\Omega, \mathcal{F}, P) be a probability space and let A,B∈FA, B \in \mathcal{F} with 0<P(B)<10 < P(B) < 1. Let Bc=Ω∖BB^c = \Omega \setminus B. Then P(A)=P(A∣B) P(B)+P(A∣Bc) (1−P(B)).P(A) = P(A \mid B) \, P(B) + P(A \mid B^c) \, (1 - P(B)).

Remarks

This is the law of total probability for the partition {B,Bc}\{B, B^c\}, together with P(Bc)=1−P(B)P(B^c) = 1 - P(B). The formula is the denominator of Bayes' theorem in the case of two hypotheses.

Explanations

L1 human

Either BB happens or it does not. So the chance of AA is its chance when BB happens times P(B)P(B), plus its chance when BB does not happen times 1−P(B)1 - P(B).

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Sources

  1. Web https://en.wikipedia.org/wiki/Law_of_total_probability, Statement