Bayes's theorem,
n. (Statistics) the fundamental result that expresses the conditional probability P(E | A) of an event E given an event A as
P(E | A) = P(A | E) P(E)/P(A);
more generally, where En is one of a set of Ei that constitute a partition of the sample space,
P(En | A) = P(A | En) P(En)/Σn[P(A | Ei) P(Ei)].
This enables prior estimates of probability to be continually revised in the light of observations.
P(E | A) = P(A | E) P(E)/P(A);
more generally, where En is one of a set of Ei that constitute a partition of the sample space,
P(En | A) = P(A | En) P(En)/Σn[P(A | Ei) P(Ei)].
This enables prior estimates of probability to be continually revised in the light of observations.