{i}. [16 points] Consider the reduced model with only one ecn'lslariatorj.r variable HR [31}: y=n+1$1+ Fit the model to data and obtain the following output from 3113: Analysis of Variance Source DF Sum of Squares Mean Square F 1tiralue Pr}F Model 1 11266264? 11266264? 6.66 6.6266 Error 28 513553626 165. 19TH] Corrected Total 29 63121666? Rt MSE 13.66374 H-S-quare 6.1T35 Dependent Mean 66.63333 Adj RSq 6.14191 Goat? Var 16.33555 Parameter Estimates Variable DF Parameter Estimate Standard Error t 1afalue Pr} 1 Intercept 1 42.38346 15.?6596 2.66 6.6121 HR 1 6.22661 6.66244 2.47 6.6266 Conduct the test to compare the full and reduced models [use or = 6.65}. State the hypotheses to he tested. the decision rule, the test statistic. and your decision. 1What can be drawn from the result of the test? 'Which model is preferred? {j}. {5 points} Fit the full model to data. The residual plot [student-iced residuals vs predicted values of y} and the normal 1;:mhahilitjyr plot of the residuals are given below. Based on these plots, do you think an}.r assumption has been violated? Justifyr your answer. {c}. [It] points} Test whether ERA {3:3} is signicant in the model with o: = 0.01. State the hy potheses to he tested, the decision rule, the test statistic, and your decision. 'What conclusion can he drawn from the result of the test? {f} [It] points} Test the overall utilityr of the model using or = [LU]. State the hypotheses to he tested, the decision rule, the test statistic, and your decision. 1What conclusion can be drawn from the result of the test?' {g}. [5 points} 1What percentage of the variation in WINS has been explained by the regression? {h}. [5 points} Calculate the Adjusted Multiple Coefcient of Determination RE. Analysis of Variance Source DF Sum of Squares Mean Square F Value Pr>F Model 3 5661.57902 Error 26 650.58765 Corrected Total 29 6312.16667 Root MSE 5.00226 R-Square Dependent Mean 80.83333 Adj R-Sq Coeff Var 6.18836 Parameter Estimates Variable DF Parameter Estimate Standard Error t Value Pr> It Intercept -21.88065 28.92622 -0.76 0.4562 HR. 0.09759 0.03572 2.73 0.0112 BA 606.30599 100.76891 6.02 <.0001 era answer the following questions using sas output. points report estimated regression equation. give an interpretation of coefficient estimate find a confidence interval for ba test whether hr is positively related to wins at level significance o="0.05." use p-value this>