Hi all I'm working on regression, in this case, just OLS. I used Birth Rate, Agriculture, Services, GDP Per Capita and Population to predict Infant Mortality. So far, there is good news. The values that gretl generates are the same values, or close enough, to the values SAS generates. There are some differences with naming outcomes, but I'm okay with that. I have some questions. The default output (what first appears when doing the model / OLS)  includes these | Mean dependent var | 20.75258 | | Sum squared resid | 19737.38 | | S.E. of regression | 9.581323 | | | | | R-squared | 0.759917 | | Adjusted R-squared | 0.754334 | | F(5, 215) | 136.1049 | | P-value(F) | 1.39E-64 | | | | | S.D. dependent var | 19.33093 | Any particular reason the Sum squared resid, S.E. of regression and the S.D. dependent var are included? The S.E. of regression is the Root MSE on SAS's default output, so that makes sense. And the output has the mean of the dependent var, so okay, the S.D. dependent var could make sense too. But why is the Sum squared resid on the default output? That's on the ANOVA (as the error sum of squares), but error mean squares is also on ANOVA but not on the default output. And the model sum of squares and mean square are also on the ANOVA but not on the default output.  That is, the ANOVA has regression sum of squares and regression mean square, and the residual sum of squares and the residual mean square. But the the only thing from the ANOVA that's on the default output is the residual sum of squares.  Why that one? Thanks Gene