sum-of-squared-residuals

The standard error of the regression (SER) is a key measure of the OLS regression line's "goodness of fit." The SER equals the square root of [sum of squared residuals (SSR) divided by the degrees of freedom (d.f.)], where d.f. is the number of observations minus the number of regression...

The ordinary least squares (OLS) regression coefficients are determined by the "best fit" line that minimizes the sum of squared residuals (SSR). David's XLS: https://trtl.bz/2uiivIm