MathLiveBayes' theorem
Gives the probability of event A after observing event B, by reversing the conditional probability P(B given A) and weighting it by the prior probability of A. It is used for updating beliefs or probabilities as new evidence arrives.
P(A \mid B) = \frac{P(B \mid A)P(A)}{P(B)}What the symbols mean
| posterior probability of A given B | |
| probability of B given A (likelihood) | |
| prior probability of A | |
| marginal probability of B, with P(B) \neq 0 |
About this formula
- FieldStatistics
- TopicProbability theory
- LevelUniversity
- Also calledBayes' rule, Bayes law, Bayesian law, Bayes-Price theorem, posterior probability formula, conditional probability inversion
- SourceWikidata Q182505
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