12.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.)

Regression Statistics
Multiple R	0.921
R Square	0.849
Adjusted R Square	0.808
Standard Error	57.000
Observations	20
ANOVA
	df	SS	MS	F	Significance F
Regression	4	273224	68306.0	21.0	5.218E-06
Residual	15	48735.4	3249.0
Total	19	321959
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%
Intercept	15.398	80.912	0.190	0.8516	-157.063	187.858
Advertising ($100s)	0.584	0.514	1.135	0.2740	-0.512	1.680
Size (Acres)	277.709	35.468	7.830	1.12E-06	202.110	353.308
Rural	-159.902	43.615	-3.666	0.0023	-252.865	-66.938
Suburban	-48.773	46.556	-1.048	0.3114	-148.005	50.459

How much variation in Traffic is explained by the regression equation (i.e., by the independent variables)?

Group of answer choices

80.8%

57.0%

92,1%

84.9%

99.3%