Mean squared error (MSE)

PrepNuggets

MSE = SSE / (n-k-1)

n: number of observations, k: number of parameters

The MSE represents the average squared difference between the observed values and the predicted values of the dependent variable. A lower MSE indicates a better fitting model, while a higher MSE indicates a poorer fitting model.

See also: ANOVA

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