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Bayes' theorem (Theorem)

Let $ (A_n)$ be a sequence of mutually exclusive events which completely cover the sample space and let $ E$ be any event. All of the events have nonzero probability ($ P(E) > 0$ and $ P(A_n) > 0$ for all $ n$). Bayes' Theorem states

$\displaystyle P(A_j\vert E) = \frac{P(A_j)P(E\vert A_j)}{\sum_i P(A_i)P(E\vert A_i)} $

for any $ A_j \in (A_n)$.

A simpler formulation is:

$\displaystyle P(A\vert B) = \frac{P(B\vert A)P(A)}{P(B)} $

For two events, $ A$ and $ B$ (also with nonzero probability).

Bibliography

1
Milton, J.S., Arnold, Jesse C., Introduction to Probability and Statistics: Principles and Applications for Engineering and the Computing Sciences, McGraw Hill, 1995.



"Bayes' theorem" is owned by akrowne.
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See Also: conditional probability

Other names:  Bayes' Rule
Keywords:  statistics, Bayes

Attachments:
proof of Bayes' Theorem (Proof) by ariels
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Cross-references: cover, events, sequence
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This is version 5 of Bayes' theorem, born on 2001-12-03, modified 2005-12-18.
Object id is 1051, canonical name is BayesTheorem.
Accessed 17545 times total.

Classification:
AMS MSC60-00 (Probability theory and stochastic processes :: General reference works )
 62A01 (Statistics :: Foundational and philosophical topics)

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