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SCENARIO 13-12
as a Project for His Business Statistics Class α\alpha

question 274

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SCENARIO 13-12
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
where
Yi = α\alpha + β\beta 1 X1i + β\beta 2 X 2i + ε\varepsilon
Y is the meter price per hour
X1 is the number of blocks to the quad
X2 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 ANOVA df SS MSF Significance F Regression 24.90352.451812.15010.0000 Residual 5511.09840.2018 Total 5716.0019 Coefficients  Standard Error t 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}{l}\begin{array}{lr}\hline{\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 \\\hline\end{array}\\\\\text { ANOVA }\\\begin{array}{lrrrrr}\hline &d f & \text { SS } &M S & 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 & &\\\hline \end{array}\\\\\begin{array}{lrrrrrr}\hline & \text { Coefficients } & \text { Standard Error } & t \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}\end{array}

-Referring to SCENARIO 13-12, what is the correct interpretation for the estimated coefficient for X2?


Definitions:

Economic Profit

The gap between the total earnings of a business and all its costs, encompassing out-of-pocket and opportunity costs.

Perfect Competitor

A Perfect Competitor refers to a hypothetical firm in a perfectly competitive market that cannot influence the market price and must accept it as given.

Short Run

A period in economics during which some factors, like capital, are fixed and cannot be changed, emphasizing immediate effects.

Price-Taker

A price-taker is a market participant that cannot influence the price of a good or service and must accept the prevailing market price.

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