15.

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 with Rural location as the base case 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	0.001	62.642	161.504

Is there a significant difference (assuming 0.05 level of significance) in traffic between a dealership in a Urban location and a dealership in a Rural location?

Group of answer choices

There is not information to answer this question

No, the difference is not significant at a p-value of 0.001

Yes, the difference is significant at a p-value of 0.004

Yes, the difference is significant at a p-value of 0.001

No, the difference is not significant at a p-value of 0.004