SCENARIO 17-7
as a Project for His Business Statistics Class $$Y _ { i } = \alpha + \beta _ { 1 } X _ { 1 i } + \beta _ { 2 } X _ { 2 i } + \beta _ { 3 } X _ { 3 i } + \varepsilon$$

SCENARIO 17-7
As a project for his business statistics class, a student examined the factors that determined parking
meter rates throughout the campus area. Data were collected for the price per hour of parking, blocks
to the quadrangle, and one of the three jurisdictions: on campus, in downtown and off campus, or
outside of downtown and off campus. The population regression model hypothesized is $$Y _ { i } = \alpha + \beta _ { 1 } X _ { 1 i } + \beta _ { 2 } X _ { 2 i } + \beta _ { 3 } X _ { 3 i } + \varepsilon$$
where
$Y$ is the meter price
$X _ { l }$ is the number of blocks to the quad
$X _ { 2 }$ is a dummy variable that takes the value 1 if the meter is located in downtown and off campus and the value 0 otherwise
$X _ { 3 }$ is a dummy variable that takes the value 1 if the meter is located outside of downtown and off campus, and the value 0 otherwise

The following Excel results are obtained.

$\begin{array}{lr}\hline {\text { Regression Statistics }} \\\hline \text { Multiple R } & 0.9659 \\\text { R Square } & 0.9331 \\\text { Adjusted R Square } & 0.9294 \\\text { Standard Error } & 0.0327 \\\text { Observations } & 58\end{array}$

$\text { ANOVA }$
$\begin{array}{lrrrrr}\hline & D f & \text { SS } & \text { MS } & F & \text { Significance } F \\\hline \text { Regression } & 3 & 0.8094 & 0.2698 & 251.1995 & 0.0000 \\\text { Residual } & 54 & 0.0580 & 0.0010 & & \\\text { Total } & 57 & 0.8675 & & & \\\hline\end{array}$

$\begin{array}{lrrrr}\hline & \text { Coefficients }& \text {Standard Error } &{t \text { Stat }} & {P \text {-value }} \\\hline \text { Intercept } & 0.5118 & 0.0136 & 37.4675 & 2.4904 \\\mathrm{X}_{1} & -0.0045 & 0.0034 & -1.3276 & 0.1898 \\\mathrm{X}_{2} & -0.2392 & 0.0123 & -19.3942 & 0.0000 \\\mathrm{X}_{3} & -0.0002 & 0.0123 & -0.0214 & 0.9829\end{array}$
-Referring to Scenario 17-7, what is the correct interpretation for the estimated coefficient for $X _ { 2 }$ ?

A) Holding the effect of the other independent variables constant, the estimated mean difference in costs between parking on campus, and parking outside of downtown and off
Campus is ?$0.24 per hour.
B) Holding the effect of the other independent variables constant, the estimated mean difference in costs between parking in downtown and off campus, and parking on campus
Is ?$0.24 per hour.
C) Holding the effect of the other independent variables constant, the estimated mean difference in costs between parking in downtown and off campus, and parking outside of
Downtown and off campus is ?$0.24 per hour.
D) Holding the effect of the other independent variables constant, the estimated mean difference in costs between parking in downtown and off campus, and parking either
Outside of downtown and off campus or on campus is ?$0.24 per hour.