Posterior variance ($\mathrm{Var}(\theta \mid y)$)

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.