For SSM the degrees of freedom are the number of predictors in the model (k), and for SSR they are the number of observations (N) minus the number of parameters being estimated (i.e., the number of b coefficients including the constant). We estimate a b for each predictor and the intercept (b0), so the total number of bs estimated will be k + 1, giving us degrees of freedom of N - (k + 1) or, more simply, N - k - 1. Thus (9.11)
