![]() The \(F\)-statistic tests the null hypothesis that the independent variable does not help explain any variance in the outcome. Looking at the top right, we see that the number of observations used to fit the model was 406. These values go into calculating the \(F\)-statistic, \(R^2\), adjusted \(R^2\), and Root Mean Square Error shown in the top right of the output. Dividing the SS column by the df (degrees of freedom) column returns the mean squares in the MS column. The box at the top left provides us with an ANOVA table that gives 1) the sum of squares ( SS) for the model, often called the regression sum of squares, 2) the residual sum of squares, and 3) the total sum of squares. The following syntax runs the regression.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |