Use the computer printout below to answer the following questions. (MUST SHOW ALL WORK) Coefficients Std. Error t-Stat P-value Intercept 729.8665 169.25751 4.3121659 0.0010099 Price -10.887 3.4952397 -3.1148078 0.0089406 Advertising 0.0465 0.0176228 2.6386297 0.0216284 Anova df SS MS F Significance F Regression 2 12332.8 6221.4 37.56127994 .000000683 Residual 12 1987.6 165.63333 Total 14 14430.4 Se=12.86986 R-squared= .862263 adj. R-Squared=.8393068 Alpha=5% a) Write and interpret the multiple regression equation b) Does the model with Price and Advertising contribute to the prediction of Y? c) Which independent variable appears to be the best predictor of sales? Explain. d) What is the number of observations used in this study? e) Find SST Assuming that the coefficient on Advertising has Ha: B1 > 0, what’s statistical decision? f) What is the standard error of estimate? Can you use this statistic to assess the model’s fit? If so, how? g) What is the coefficient of determination, and what does it tell you about the regression model? h) What is the coefficient of determination, adjusted for degrees of freedom? What do this statistic and the statistic referr to in part (g) tell you about how well this model fits that data. i) Test the overall utility of the model. What does the p-value of the test statistic tell you?