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A Real Estate Magazine Reported the Results of a Regression

Question 38

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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, 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 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 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. x. The results of the simple linear regression are provided below. 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. Interpret the estimate 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. , 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.

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