Refer to the accompanying table, which was obtained using data from homes sold.

Question

Refer to the accompanying table, which was obtained using data from homes sold. The response (y) variable is selling price (in dollars). The predictor (x) variables are LP (list price in dollars), LA (living area of the home in square feet), and LOT (lot size in acres) If only one predictor (x) ariable is used to predict the selling price, which single variable is best? Why? EEE Click the icon to view the various regression equations. Select the best choice. O A. The best single predictor variable is LOT because the associated regression equation has the highest P-value of o.047 and the lowest adjusted R2 of 0.185. O B. The best single predictor variable is LP because the associated regression equation has the lowest P-value of 0.000 and the highest adjusted R2 of 0.987 O C. The best single predictor variable is LA because the associated regression equation has the lowest P-value of o.000 and the lowest adjusted R2 of 0.603 of the equations with a P-value of 0.000. C D. None of the single predictor variables can be used to predict the selling price

Explanation / Answer

The highest adjusted R2 in case of single variable is with LP. Hence,

The best single predictor is LP.

Option B is correct.

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