17. An automobile manufacturer has 20 franchised dealers in a large metropolitan area. To study factors influencing the amount of customer traffic, data were collected on customer traffic per week, the amount of newspaper and TV advertising by each dealer (shown in $100s), the size of their physical facilities (in acres), and the location of the dealership (Urban, Suburban or Rural).
Assume that the regression analysis resulted in the following results. (Note that a different data set was used to find these results than for earlier problems where the data were given.)
SUMMARY OUTPUT
Regression Statistics
Multiple R: 0.905
R Square: 0.819
Adjusted R Square: 0.770
Standard Error: 36.292
Observations: 20
ANOVA
df:
SS:
MS:
F:
Significance F:
Regression: 4
89114.89
22278.7
16.915
1.9709E-05
Residual: 15
19756.91
1317.1
Total: 19
108871.80
Coefficients
Standard Error
t Stat
P-value
Lower 95%
Upper 95%
Intercept: -47.840
54.582
-0.876
0.395
-164.179
68.499
Advertising ($100s): 0.689
0.368
1.870
0.081
-0.096
1.474
Size (Acres): 167.273
21.465
7.793
0.000
121.521
213.025
Suburban: 77.075
22.958
3.357
0.004
28.141
126.008
Urban: 112.073
23.191
4.833
0.000
62.642
161.504
Which of the independent variables are significantly related to Traffic at the .05 level of significance?
Group of answer choices
Only Advertising ($100s)
None of the independent variables
Advertising ($100s), Suburban, Urban
Size (Acres), Suburban, Urban
All of the independent variables