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 where Y is the meter price is the number of blocks to the quad is a dummy variable that takes the value 1 if the meter is located in downtown and off campus and the value 0 otherwise 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 Suppose that whether the meter is located on campus is an important explanatory factor. Why should the variable that depicts this attribute not be included in the model?
A)Its inclusion will introduce autocorrelation.
B)Its inclusion will introduce collinearity.
C)Its inclusion will inflate the standard errors of the estimated coefficients.
D)Both (b)and (c).

Question

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  where Y is the meter price  is the number of blocks to the quad  is a dummy variable that takes the value 1 if the meter is located in downtown and off campus and the value 0 otherwise  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 Suppose that whether the meter is located on campus is an important explanatory factor. Why should the variable that depicts this attribute not be included in the model?
A)Its inclusion will introduce autocorrelation. 
B)Its inclusion will introduce collinearity. 
C)Its inclusion will inflate the standard errors of the estimated coefficients. 
D)Both (b)and (c).

Quizplus · Accepted Answer

The Answer of 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  where Y is the meter price  is the number of blocks to the quad  is a dummy variable that takes the value 1 if the meter is located in downtown and off campus and the value 0 otherwise  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 Suppose that whether the meter is located on campus is an important explanatory factor. Why should the variable that depicts this attribute not be included in the model?
A)Its inclusion will introduce autocorrelation. 
B)Its inclusion will introduce collinearity. 
C)Its inclusion will inflate the standard errors of the estimated coefficients. 
D)Both (b)and (c).

As a Project for His Business Statistics Class, a Student