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SCENARIO 14-12 as a Project for His Business Statistics Class Yi=α+β1X1i+β2X2i+εY _ { i } = \alpha + \beta _ { 1 } X _ { 1 i } + \beta _ { 2 } X _ { 2 i } + \varepsilon

question 12

Multiple Choice

SCENARIO 14-12 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 whether the parking is on or off campus. The population regression model hypothesized is Yi=α+β1X1i+β2X2i+εY _ { i } = \alpha + \beta _ { 1 } X _ { 1 i } + \beta _ { 2 } X _ { 2 i } + \varepsilon
where
YY is the meter price per hour
XlX _ { l } is the number of blocks to the quad
X2X _ { 2 } is a dummy variable that takes the value 1 if the meter is located on campus and 0 otherwise

The following Excel results are obtained.

 Regression Statistics  Multiple R 0.5536 R Square 0.3064 Adjusted R Square 0.2812 Standard Error 0.4492 Observations 58\begin{array}{lr}{\text { Regression Statistics }} \\\hline \text { Multiple R } & 0.5536 \\\text { R Square } & 0.3064 \\\text { Adjusted R Square } & 0.2812 \\\text { Standard Error } & 0.4492 \\\text { Observations } & 58\end{array}

ANOVA
df SS  MS  F  Significance F  Regression 24.90352.451812.15010.0000 Residual 5511.09840.2018 Total 5716.0019\begin{array}{lrrrrr} & d f &{\text { SS }} & \text { MS } & {\text { F }} & \text { Significance F } \\\hline \text { Regression } & 2 & 4.9035 & 2.4518 & 12.1501 & 0.0000 \\\text { Residual } & 55 & 11.0984 & 0.2018 & & \\\text { Total } & 57 & 16.0019 & & &\end{array}

 Coefficients  Standard Error  Stat  P-value  Lower 99%  Upper 99%  Intercept 1.65000.20288.13590.00001.10892.1912 Block 0.25040.05294.73550.00000.39150.1093 Campus 0.15520.12971.19660.23660.19080.5011\begin{array}{lrrrrrr} & \text { Coefficients } & \text { Standard Error } & {\text { Stat }} & \text { P-value } & \text { Lower 99\% } & \text { Upper 99\% } \\\hline \text { Intercept } & 1.6500 & 0.2028 & 8.1359 & 0.0000 & 1.1089 & 2.1912 \\\text { Block } & -0.2504 & 0.0529 & -4.7355 & 0.0000 & -0.3915 & -0.1093 \\\text { Campus } & 0.1552 & 0.1297 & 1.1966 & 0.2366 & -0.1908 & 0.5011 \\\hline\end{array}

-Referring to Scenario 14-12, what is the correct interpretation for the estimated coefficient for X2X _ { 2 } ?


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