The mean square regression is found by dividing the sum of squares regression by the number of independent variables minus one (k - 1).

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The mean square regression is found by dividing the sum of squares regression by the degrees of freedom associated with the regression, which is typically the number of independent variables (k), not k - 1. The formula for mean square regression is the sum of squares due to regression (SSR) divided by the degrees of freedom for the regression, which is usually just k, if it's a simple linear regression, then it's divided by 1.

The Mean Square Regression Is Found by Dividing the Sum