14. 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 Urban 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	0.690
R Square	0.477
Adjusted R Square	0.337
Standard Error	98.348
Observations	20
ANOVA
	df	SS	MS	F	Significance F
Regression	4	132202.55	33050.6	3.417	0.035534399
Residual	15	145084.25	9672.3
Total	19	277286.80
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%
Intercept	86.328	141.095	0.612	0.550	-214.408	387.064
Advertising ($100s)	0.459	1.548	0.297	0.771	-2.839	3.758
Size (Acres)	157.596	60.391	2.610	0.020	28.875	286.317
Rural	-82.161	50.924	-1.613	0.127	-190.704	26.382
Suburban	-123.358	71.600	-1.723	0.105	-275.970	29.254

All other things being equal, what do you estimate the difference in traffic will be between a dealership in a Rural location compared to the traffic in an Urban location? If you estimate that the traffic will be higher for a Rural location, indicate a positive number; otherwise use a negative number.

Group of answer choices

82.161

-82.161

-4.167

There is not enough information to answer this question--we would need to re-run the regression with Urban as a variable.

4.167