A retail manager is interested in the relationship between store sales (Y, in $1000s) and the following predictor variables: average inventory level (X1, in $1000s), population within 3 miles of store (X2 , in 1000s), median household income within 3 miles of store (X3, in $1000s), and an indicator of whether there is a direct competitor within 1 mile of the store (X4=1 if yes, 0 if no). The following EXCEL output is obtained, based on a sample of 25 stores in her chain during June.

ANOVA

df

SS

MS

F

Significance F

Regression

4

3125.76

781.4399

111.3737

.00000

Residual

20

140.3276

7.016379

Total

24

3266.087

Coefficients

Standard Error

t Stat

P-value

Intercept

-8.74

4.018179

-2.17583

0.04173

Inventory

0.49

0.117605

4.159726

0.000484

Pop

1.06

0.15798

6.725044

.0000

Income

0.95

0.082553

11.5506

.0000

Compete

-20.65

1.205259

-17.1327

.0000

5.

She wishes to test whether any of these predictors are associated with sales. Give the test statistic and her decision (and why) for the test at the =0.05 significance level.

a) Test statistic = 111.37, conclude at least one of the predictors is associated with sales since P-value< .05

b) Test statistic = -2.176, conclude at least one of the predictors is associated with sales since P-value< .05

c) Test statistic = 111.37, don’t conclude any of the predictors are associated with sales since P-value< .05

d) Test statistic = -2.176, don’t conclude any of the predictors are associated with sales since P-value< .05

16. Give the predicted sales for a store with X1=25 , X2=20 , X3=40 , and a direct competitor is within 1 mile.

a) 62.71

b) 58.11

c) -26.89

d) 42.06

e) 83.36