The normal linear regression model Y =o+1x1 +--- +13ka+ is used to analyze a data set and we have the following results: Model # X Variables in model (if SSRIS 1 one 53 3.97 3 2 X] 52 3.4900 3 X2 52 2.5702 4 X3 52 2.2154 5 X4 52 1.3777 6 X. . X2 51 2.2324 7 XI . X3 51 1.4073 8 X. . X4 51 1.3759 9 X2. X3 51 0.7431 10 X2. X4 51 1.3922 11 X3.X4 51 1.2455 12 X1.X2.X3 50 0.1099 13 X1.X2. X4 50 1.3905 14 X1.X3.X4 50 1.1157 15 X2.X3. X4 50 0.4653 16 X1.X2.X3. X4 49 0.1093 a. What is the sample size of this data set? b. Excluding Model (16). which model would you remtnmend to use? \"my? o. Is Model {13} a signicant model? C]. At 10% level. should X1 and X2 be jointly added into Model (5)? e. What is the proportion of explained variations dropped when X1 is dropped from Model (12)? 1\". Obtain the coefcient- of determination for Model {9). Based on your result. is Model [9} a good model? Why? g. Consider the sequence of adding the esplanatory 1variables into the model is X1. X3. X4 and nally X2. Clearly state the 4 models and report the Type I sum of squarrs [sequential sum of squares} for the four models. h. Re-do part (g) but. the sequence is X1. X2. X3 and X4