Consider Table 12.5.15, showing the partial results from a multiple regression analysis that explains the annual sales of 25 grocery stores by some of their characteristics. The variable €œmall€ is 1 if the store is in a shopping mall and 0 otherwise. The variable €œcustomers€ is the number of customers per year.
a. To within approximately how many dollars can you predict sales with this regression model?
b. Find the predicted sales for a store that is in a shopping mall and has 100,000 customers per year.
c. Does each of the explanatory variables have a significant impact on sales? How do you know?
d. What, exactly, does the regression coefficient for customers tell you?
e. Does the location (mall or not) have a significant impact on sales, comparing two stores with the same number of customers? Give a brief explanation of why this might be the case.
f. Approximately how much extra in annual sales comes to a store in a mall, as compared to a similar store not located in a mall?

TABLE 12.5.15 Multiple Regression Results for Grocery Stores' Annual Sales The regression equation is Sales -36589209475 Mall10.3 Customers Predictor Constant Mall Customers Coeff StDev 82957 77040 t-ratio -0.44 2.72 2.30 36589 0.663 0.013 0.031 209475 10.327 4.488 S-183591 R-sq-39.5% Rsqad)-34.0%