Bayes' theorem

Bayes' theorem, also known as Bayes' Law or Bayes' rule, is a theorem of probability in statistics. The theorem describes how the conditional probability of each of a set of possible causes for a given observed outcome can be computed from the knowledge of the probability of each cause and the conditional probability of the outcome of each cause. In mathematical term it is expressed as -

P(A|B) = {P(A)xP(B|A)}/P(B)

How likely A may happen given that B happens is written as P(A|B).
How likely A may happen on its own is written P(A).
How likely B may happen on its own is written P(B).
How often B happens given that A happens is written as P(B|A).

The theorem is named after the English mathematician Thomas Bayes (1702-61) who first used conditional probability to provide an algorithm that uses evidence to calculate limits on an unknown parameter, published as An Essay towards solving a Problem in the Doctrine of Chances (1763).