In multiple regression, the standard error of estimate is defined by $s _ { \varepsilon } = \sqrt { \alpha n E / ( n - k ) }$ , where n is the sample size and k is the number of independent variables.

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The standard error of estimate in multiple regression is defined as $s _ { \varepsilon } = \sqrt { SSE / ( n - k - 1 ) }$, where SSE is the sum of squared errors, n is the sample size, and k is the number of independent variables.

In Multiple Regression, the Standard Error of Estimate Is Defined sε=αnE/(n−k)s _ { \varepsilon } = \sqrt { \alpha n E / ( n - k ) }sε​=αnE/(n−k)​

In Multiple Regression, the Standard Error of Estimate Is Defined $s _ { \varepsilon } = \sqrt { \alpha n E / ( n - k ) }$