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Author Question: A real estate magazine reported the results of a regression analysis designed to predict the price ... (Read 154 times)

dbose

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on: Jan 16, 2020
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.
= 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.
◦ About 95% of the observed sale prices fall within $96,600 of the least squares line.
◦ All residential properties in Virginia will sell for at least $96,600.
◦ For every 1-sq ft. increase in GLA, we expect a property's sale price to increase $96,600.
◦ There is no practical interpretation, since a gross living area of 0 is a nonsensical value.
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Marked as best answer by dbose on Jan 16, 2020

allisonblackmore

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Reply #1 on: Jan 16, 2020
Lorsum iprem. Lorsus sur ipci. Lorsem sur iprem. Lorsum sur ipdi, lorsem sur ipci. Lorsum sur iprium, valum sur ipci et, vala sur ipci. Lorsem sur ipci, lorsa sur iprem. Valus sur ipdi. Lorsus sur iprium nunc, valem sur iprium. Valem sur ipdi. Lorsa sur iprium. Lorsum sur iprium. Valem sur ipdi. Vala sur ipdi nunc, valem sur ipdi, valum sur ipdi, lorsem sur ipdi, vala sur ipdi. Valem sur iprem nunc, lorsa sur iprium. Valum sur ipdi et, lorsus sur ipci. Valem sur iprem. Valem sur ipci. Lorsa sur iprium. Lorsem sur ipci, valus sur iprem. Lorsem sur iprem nunc, valus sur iprium.
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dbose

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Reply 2 on: Jan 16, 2020
Gracias!

diana chang

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Reply 3 on: Yesterday
Excellent

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