The improvement in prediction resulting from using the linear model rather than the mean is calculated as the difference between SST and SSR (Figure 9.5, bottom). This difference shows us the reduction in the inaccuracy of the model resulting from fitting the regression model to the data. This improvement is the model sum of squares (SSM).
