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Consider Table 12 5 15 showing the partial results from a multiple

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 “mall” is 1 if the store is in a shopping mall and 0 otherwise. The variable “customers” 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?

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?

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