Mean Squared Error - Alternative Usages

Alternative Usages

In regression analysis, the term mean squared error is sometimes used to refer to the estimate of error variance: residual sum of squares divided by the number of degrees of freedom. This is an observed quantity given a particular sample (and hence is sample-dependent), whereas the definition above is a function of the parameters of the probability distribution of an unknown parameter. For more details, see errors and residuals in statistics.

Also in regression analysis, "mean squared error", often referred to as "out-of-sample mean squared error", can refer to the mean value of the squared deviations of the predictions from the true values, over an out-of-sample test space, generated by a model estimated over a particular sample space. This also is an observed quantity, and it varies by sample and by out-of-sample test space.