What's new

# sum-of-squared-residuals

1. ### YouTube T2-16 Regression: standard error of regression

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...
2. ### YouTube T2-15 Linear regression: OLS coefficients minimize the SSR

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