# AP Statistics Curriculum 2007 Bayesian Prelim

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Bayes Theorem

Bayes theorem is associated with probability statements that relate conditional and marginal properties of two random events. These statements are often written in the form "the probability of A, given B" and denoted P(A|B) = P(B|A)*P(A)/P(B) where P(B) not equal to 0.

P(A) is often known as the Prior Probability (or as the Marginal Probability)

P(A|B) is known as the Posterior Probability (Conditional Probability)

P(B|A) is the conditional probability of B given A (also known as the likelihood function)

P(B) is the prior on B and acts as the normalizing constant. In the Bayesian framework, the posterior probability is equal to the prior belief on A times the likelihood function given by P(B|A).