76. How do we use the f-test to compare models

The f-test can be used to compare models by measuring the ratio of their explained sum of squares to their residual sum of squares. The f-test can help determine if the addition of variables or parameters to a model significantly improves its ability to explain variation in the observed data. The f-test will calculate the ratio of the differences in explained sums of squares divided by the residual sums of squares for two models. If the f-value is greater than the corresponding critical value from the F-distribution the model with the higher ratio is considered to provide a better fit.