I'm reviewing
Bayes' theorem and related topics for the upcoming
GDAT class. In its simplest form, Bayes' theorem is a statement about conditional probabilities. The probability of A, given that B has occurred, is expressed as:
Pr
In Bayesian language,
\Pr(A|B) is called the
posterior probability,
\Pr(A) the
prior probability, and
\Pr(B|A) the likelihood (essentially a normalization factor).
Source: Wikipedia