The comparative R squared statistic is a new way to test how important additional factors are in predicting outcomes. It compares the accuracy of two models, one with more variables and one with fewer. This statistic is better than the traditional F test when data is not normally distributed. The test works well even with small amounts of data, showing accurate results without errors.