a) Fill in the blanks in the following tables. The column labeled \"Seq SS\" represents \"sequential sums of squares\" (measures the reduction in the SS when a term is added to a model that contains only the terms before it), while the column labeled \"Adj SS\" represents \"adjusted sums of squares\" (measures the reduction in the SS for each term relative to a model that contains all of the remaining terms). [Hint: The t-statistics in the Coefficients table assume all other predictors are included in the model, so if we square these we get the F-statistics in the Anova table based on Adjusted Sums of Squares.] Source df Seq SS Adj SS F-statistic p-value based on Adj based on Adj SS SS Regressio 3 100.866 35.14 0.000 n X1 1 67.444 33.031 34.52 0.000 X2 1 3.883 X3 1 30.88 0.000 Error 93 ---------Total 96 189.842 189.842 ---------Coefficients Term Constant X1 X2 X3 Coef 0.58 0.34 -0.01 0.06 SE coef 1.24 0.058 0.0245 0.0103 t-statistic 0.45 5.88 p-value 0.652 0.000 5.56 0.000 b) Calculate SSR(X3|X1), that is the sequential sum of squares obtained by adding X3 to a model already containing only the predictor X 1. Show your work. c) Calculate the value of an F-statistic for testing H 0: 2 = 3 = 0 within the model Yi = 0 + 1 Xi,1 + 2 Xi,2 + 3 Xi,3 + i. It is not necessary to carry out the test - just calculate the value of F. Show your work. d) Calculate the value of the coefficient of partial determination R2Y,2|1