Editing Mean squared error (section)

==Applications==
Minimizing MSE is a key criterion in selecting estimators; see [[minimum mean-square error]]. Among unbiased estimators, minimizing the MSE is equivalent to minimizing the variance, and the estimator that does this is the [[minimum variance unbiased estimator]]. However, a biased estimator may have lower MSE; see [[estimator bias]].

In [[statistical modelling]] the MSE can represent the difference between the actual observations and the observation values predicted by the model. In this context, it is used to determine the extent to which the model fits the data as well as whether removing some explanatory variables is possible without significantly harming the model's predictive ability.

In [[forecasting]] and [[prediction]], the [[Brier score]] is a measure of [[forecast skill]] based on MSE.