TABLE 14-13
as a Project for His Business $Y_{i}=\alpha+\beta_{1} X_{1 i}+\beta_{2} X_{2 i}+\beta_{3} X_{3 i}+\varepsilon$

question 159

Multiple Choice

TABLE 14-13
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;
^X1 ^{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;
^X3 ^{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.
$\begin{array}{lc}\hline \text {Regression Statistics } \\\hline \text {Multiple R} & 0.9659 \\ \text {R Square}& 0.9331 \\ \text {Adjusted R Square} & 0.9294 \\ \text {Standard Error }& 0.0327 \\ \text {Observations} & 58 \\\hline\end{array}$

ANOVA
$\begin{array}{lrcccr}\hline & \text { d f } & \text { SS} & \text { M S } & \text { F }& \text { Significance F }\\\hline \text { Regression} & 3 & 0.8094 & 0.2698 & 251.1995 & 1.0964 \mathrm{E}-31 \\ \text { Residual }& 54 & 0.0580 & 0.0010 & & \\ \text { Total} & 57 & 0.8675 & & & \\\hline\end{array}$

$\begin{array}{lcccl}\hline & \text { Coefficients} & \text {Standard Error }& \text {t Stat }& \text { p-value} \\\hline \text {Intercept} & 0.5118 & 0.0136 & 37.4675 & 2.4904 \\\mathrm{X1 } & -0.0045 & 0.0034 & -1.3276 & 0.1898 \\\mathrm{X2 } & -0.2392 & 0.0123 & -19.3942 & 5.3581 \mathrm{E}-26 \\\mathrm{X3 } & -0.0002 & 0.0123 & -0.0214 & 0.9829 \\\hline\end{array}$

-Referring to Table 14-13, if one is already outside of downtown and off campus but decides to park 3 more blocks from the quad, the estimated average parking meter rate will

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Definitions:

Holding Constant

Holding constant is a method used in analysis where certain variables are kept unchanged in order to isolate the effects of other variables.

Independent Variables

Variables in a statistical model that are presumed to influence or cause changes in another variable, without being affected by it.

Increase

Increase refers to the action of becoming larger or greater in size, number, value, or amount.

Standard Error

A statistical measure that describes the accuracy with which a sample distribution represents a population, specifically the standard deviation of the sampling distribution of a statistic.