Posteriors

Posterior distributions (or posteriors) represent the results of a Bayesian analysis. The posteriors describe the updated probability distribution for a parameter that is calculated by combining the prior distribution with new data; they represent the new, refined beliefs about the parameter after all available evidence has been taken into account. The posteriors are used to make subsequent inferences and predictions. This is slightly different to a posteriori statistical tests, which are tests that were not planned prior to data collection.

Also, see priors.