Posterior probability

In Bayesian inference, the updated probability distribution of a parameter or hypothesis after observing data. Derived via Bayes' theorem as the product of the prior and the likelihood, normalized: P(θ|data) ∝ P(data|θ) × P(θ). It forms the primary output of Bayesian analysis.