P(A|B) = P(B|A)P(A)/P(B) Is a rule from statistics. In Bayesian speak this usually becomes P(prior|data) = P(data|prior)P(prior)/P(data) or P(prior|

P(A|B) = P(B|A)P(A)/P(B) Is a rule from statistics. In Bayesian speak this usually becomes P(prior|data) = P(data|prior)P(prior)/P(data) or P(prior|data) proportional to P(data|prior)P(prior) where P(prior|data) is also called the "posterior". The main idea is that you have some idea of "the prior" and you update it with your data to "update the prior" to get the posterior. This is probably not what you were looking for but this is it.