P(H|D)/P(-H|D) = P(D|H) • P(D|-H) • P(H)/P(-H) Posterior Odds = Likelihood Ratio • Prior Odds The Bayesian belief-updating equation In simple terms, the theorem says that your new belief should depend on two things—your prior belief (and all the knowledge that informed it) multiplied by the “diagnostic value” of the new information.
