A real estate magazine reported the results of a regression analysis designed to predict the price (y), measured in dollars, of residential properties recently sold in a northern Virginia subdivision. One independent variable used to predict sale price is GLA, gross living area (x), measured in square feet. Data for 157 properties were used to fit the model, = + x. The results of the simple linear regression are provided below. Interpret the estimate of , the y-intercept of the line.
A) For every 1-sq ft. increase in GLA, we expect a property's sale price to increase $96,600.
B) About 95% of the observed sale prices fall within $96,600 of the least squares line.
C) There is no practical interpretation, since a gross living area of 0 is a nonsensical value.
D) All residential properties in Virginia will sell for at least $96,600.

Question

A real estate magazine reported the results of a regression analysis designed to predict the price (y), measured in dollars, of residential properties recently sold in a northern Virginia subdivision. One independent variable used to predict sale price is GLA, gross living area (x), measured in square feet. Data for 157 properties were used to fit the model,  =  +  x. The results of the simple linear regression are provided below.  Interpret the estimate of  , the y-intercept of the line.
A) For every 1-sq ft. increase in GLA, we expect a property's sale price to increase $96,600. 
B) About 95% of the observed sale prices fall within $96,600 of the least squares line. 
C) There is no practical interpretation, since a gross living area of 0 is a nonsensical value. 
D) All residential properties in Virginia will sell for at least $96,600.

Quizplus · Accepted Answer

The Answer of A real estate magazine reported the results of a regression analysis designed to predict the price (y), measured in dollars, of residential properties recently sold in a northern Virginia subdivision. One independent variable used to predict sale price is GLA, gross living area (x), measured in square feet. Data for 157 properties were used to fit the model,  =  +  x. The results of the simple linear regression are provided below.  Interpret the estimate of  , the y-intercept of the line.
A) For every 1-sq ft. increase in GLA, we expect a property's sale price to increase $96,600. 
B) About 95% of the observed sale prices fall within $96,600 of the least squares line. 
C) There is no practical interpretation, since a gross living area of 0 is a nonsensical value. 
D) All residential properties in Virginia will sell for at least $96,600.

A Real Estate Magazine Reported the Results of a Regression