ANOVAa \"n"- Suares Regression 2391.564 {1.000055 1 Residual Total 3429.938 a. Dependent Variable: Mass b. Predictors: [Constant], Age hmmammd cmmmmts -H 1 (Domain 155.143 10.944 Age -1.D13 .173 a} (1 mark} What is the estimated simple linear regression model? In other words, what is the sample linear regression equation? b] [1 mark] What percentage of variability in muscle mass is explained by age or is explained by the regression model? 1:] (2 marks] What is the standard error of the model [or the estimated standard deviation of the errors)? d) (6 marks) Is the overall regression model significant? In other words, is there a linear relationship between muscle mass and age? At the 1% significance level, carm out the most appropriate test, using the F-distribution, to answer this question. SHOW ALL STEPS. Give both the exact Pvaiue based on the computer output and the Pvalue obtained from the appropriate statistical table. e] [2 marks] Calculate the linear correlation coefficient for the relationship between muscle mass and age. Calculate (if and give the exact Pvalue based on the computer output. You do "NOT\" need to show all steps of a hypothesis test. f] (5 marks} At the 1% significance level, test the hypothesis that there is a negative relationship between muscle mass and age. Carp; out the most appropriate test, using the bdistribution to answer this question. SHOW ALL STEPS. Give both the exact Pvalue based on the computer output and the Pvalue obtained from the appropriate statistical table. g] (1 mark] Compare the test statistic from part [d] to the test statistic obtained in part If]. How are they related