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,? = β0 + β1x. The results of the simple linear regression are provided below. y = 96,600 +22.5x s = 6500 r2 = -0.77 t = 6.1 (for testing β1) Interpret the estimate of β0 the y-intercept of the line. a. About 95% of the observed sale prices fall within $96,600 of the least squares line. b. There is no practical interpretation, since a gross living area of 0 is a nonsensical value. c. All residential properties in Virginia will sell for at least $96,600. d. For every 1-sq ft. increase in GLA, we expect a property's sale price to increase $96,600.
) A real estate magazine reported the results of a
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,? = β0 + β1x.
The results of the simple linear regression are provided below.
y = 96,600 +22.5x s = 6500 r2 = -0.77 t = 6.1 (for testing β1)
Interpret the estimate of β0 the y-intercept of the line.
a. About 95% of the observed sale prices fall within $96,600 of the least squares line.
b. There is no practical interpretation, since a gross living area of 0 is a nonsensical
value.
c. All residential properties in Virginia will sell for at least $96,600.
d. For every 1-sq ft. increase in GLA, we expect a property's sale price to increase
$96,600.
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