The normal linear regression model Y = Bo + BIX1 + ... + 3xXx te is used to analyze a data set and we have the following results: Model # X variables in model df SSRes 1 None 53 3.9728 X1 52 3.4960 X2 2.5762 X3 52 2.2154 XA 52 1.8777 X1, X2 51 2.2324 X1, X3 51 1.4073 X1, XA 51 1.8759 X2, X3 51 0.7431 X2, XA 51 1.3922 11 X3, XA 51 1.2455 12 X1, X2, X3 50 0.1099 13 X1, X2, XA 50 1.3905 14 X1, X3, XA 50 1.1157 15 X2, X3, X 50 0.4653 16 X1, X2, X3, XA 49 0.1098 f. Obtain the coefficient of determination for Model (9). Based on your result, is Model (9) a good model? Why? g. Consider the sequence of adding the explanatory variables into the model is X1, X3, X4 and finally X2. Clearly state the 4 models and report the Type I sum of squares (sequential sum of squares) for the four models. h. Re-do part (g) but the sequence is X1, X2, X3 and X4