<Ul> <Li> 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 . </Li> <Li> 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 . </Li> </Ul> <Li> 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 . </Li> <Li> 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 . </Li> <P> Squared error loss is one of the most widely used loss functions in statistics, though its widespread use stems more from mathematical convenience than considerations of actual loss in applications . Carl Friedrich Gauss, who introduced the use of mean squared error, was aware of its arbitrariness and was in agreement with objections to it on these grounds . The mathematical benefits of mean squared error are particularly evident in its use at analyzing the performance of linear regression, as it allows one to partition the variation in a dataset into variation explained by the model and variation explained by randomness . </P>

Which of the following is not a measure of variance in the forecast error