The sum of squares of residuals is not r square. The sum of squares of residuals is to clearly explain the influence of variables and random errors. Statistically, the difference between a data point and its corresponding position on the regression line is called residual, and the sum of squares of each residual is called sum of squares of residuals, which indicates the influence of random errors. R square refers to goodness of fit, that is, the fitting degree of the regression line to the observed value.