Consider the regression below (below) that was estimated on weekly data over a 2 -year period on a sample of Kroger stores for Pepsi carbonated soft drinks. The dependent variable is the log of Pepsi volume per MMACV. There are 53 stores in the dataset (data were missing for some stores in some weeks). Please answer the following questions about the regression output. Model Summary (b) a Predictors: (Constant), Mass stores in trade area, Labor Day dummy, Pepsi advertising days, Store traffic, Memorial Day dummy, Pobsi display days, Coke advertising days, Log of Pepsi price, Coke display days, Log of Coke price b Dependent Variable: Log of Pepsi volume/MM ACV ANOVA(b) a Predictors: (Constant), Mass stores in trade area, Labor Day dummy, Pepsi advertising days, Store traffic, Memorial Day dummy, Pepsi display days, Coke advertising days, Log of Pepsi price, Coke display days, Log of Coke price b Dependent Variable: Log of Pepsi volume/MMACV Coefficients(a) a Dependent Variable: Log of Pepsi volume/MMACV Questions (a) Comment on the goodness of fit and significance of the regression and of individual variables. What does the ANOVA table reveal? (b) Write out the equation and interpret the meaning of each of the parameters. (c) What is the price elasticity? The cross-price elasticity with respect to Coke price? Are these results reasonable? Explain. (d) What do the results tell you about the effectiveness of Pepsi and Coke display and advertising? (e) What are the 3 most important variables? Explain how you arrived at this conclusion. (f) What is collinearity? Is collinearity a problem for this regression? Explain. If it is a problem, what action would you take to deal with it? (g) What changes to this regression equation, if any, would you recommend? Explain