Posterior variance
= Posterior variance
{title2=$\operatorname{Var}(\theta\mid y)$}
A <posterior variance> is the <variance> of a parameter under its <Bayesian posterior>, namely $\mathbb E[(\theta-\mathbb E[\theta\mid y])^2\mid y]$ when finite. It describes remaining uncertainty after observing data and is distinct from the repeated-sampling variance of a fitted estimator.