a priori distribution

In Bayesian analysis, an a priori distribution is a probability distribution assigned to a parameter before any new evidence is considered. This distribution represents prior beliefs or existing knowledge about the parameter's possible values. It's a foundational step in Bayesian inference, where this prior distribution is combined with observed data (evidence) using Bayes' theorem to produce a posterior distribution. The posterior distribution then reflects updated beliefs about the parameter after incorporating the new evidence. This approach allows for the integration of subjective opinions or objective data to form initial probability assignments.12