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 + β 1 X 1i + β 2 X 2i + ε
where
Y is the meter price per hour
X 1 is the number of blocks to the quad
X 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.
Statistics Regression
Multiple R 0.5536
R Square 0.3064
Adjusted R Square 0.2812
Standard Error 0.4492
Observations 58

ANOVA
df SS MS F Significance F
Regression 2 4.9035 2.4518 12.1501 0.0000
Residual 55 11.0984 0.2018
Total 57 16.0019

Coefficients Standard Error t Stat P-value Lower 99% Upper 99%
Intercept 1.6500 0.2028 8.1359 0.0000 1.1089 2.1912
Block -0.2504 0.0529 -4.7355 0.0000 -0.3915 -0.1093
Campus 0.1552 0.1297 1.1966 0.2366 -0.1908 0.5011
Referring to Scenario 13-12, what is the correct interpretation for the estimated coefficient for X 2?
Holding the effect of the distance from the quad constant, the estimated mean costs for parking on campus is $0.16 per hour more than parking off campus.
Holding the effect of the distance from the quad constant, the estimated mean costs for parking on campus is $0.16 per hour more than parking off campus for each additional block away from the quad.
Holding the effect of the distance from the quad constant, the estimated mean costs for parking off campus is $0.16 per hour more than parking on campus for each additional block away from the quad.
Holding the effect of the distance from the quad constant, the estimated mean costs for parking off campus is $0.16 per hour more than parking on campus.

For simple linear regression, the chief null hypothesis is H0 : β1 = 0, and the corresponding alternative hypothesis is H1 : β1 = 0. If this null hypothesis is true, then, from E(Y ) = β0 + β1x we can see that the population mean of Y is β0 for every x value, which tells us that x has no effect on Y .

Holding the effect of the distance from the quad constant, the estimated mean costs for parking on campus is $0.16 per hour more than parking off campus.

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