Problem: The owner of a pizza restaurant chain would like to predict sales of his specialty deep dish pizza. He gathered data on the monthly sales of deep dish pizzas at his restaurant and observations on other potentially relevant variables for each of his 15 outlets in central Penn. Data is attached.
1) Estimate a multiple regression model between the quantity sold (Y) and the following explanatory variables: avg price of deep-dish pizzas, monthly advertising expenditures, and disposable income per household in the surrounding areas around his outlets.
2) Which of the variable in this model have regression coefficients that are statistically different from 0 at the 5% significance level?
3) Given your findings in part 2, which variables, if any, would you choose to remove from the model estimated in part A? explain.
| Outlet_Number |
Quantity_Sold |
Average_Price |
Monthly_Advertising_Expenditures |
Disposable_Income_per_Household |
| 1 |
85,300 |
$10.14 |
$64,800 |
$42,100 |
| 2 |
40,500 |
$10.88 |
$42,800 |
$38,300 |
| 3 |
61,800 |
$12.33 |
$58,600 |
$41,000 |
| 4 |
50,800 |
$12.70 |
$46,500 |
$43,300 |
| 5 |
60,600 |
$12.29 |
$50,700 |
$44,000 |
| 6 |
79,400 |
$9.79 |
$60,100 |
$41,200 |
| 7 |
71,400 |
$11.26 |
$55,600 |
$41,700 |
| 8 |
70,700 |
$11.23 |
$57,900 |
$43,600 |
| 9 |
55,600 |
$11.97 |
$52,100 |
$39,900 |
| 10 |
70,900 |
$12.07 |
$60,700 |
$44,800 |
| 11 |
77,200 |
$10.68 |
$64,400 |
$41,800 |
| 12 |
63,200 |
$12.49 |
$55,600 |
$44,200 |
| 13 |
71,100 |
$12.36 |
$60,900 |
$40,100 |
| 14 |
55,500 |
$9.96 |
$47,200 |
$39,100 |
| 15 |
42,100 |
$11.77 |
$46,100 |
$38,000 |