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 dolars). The predictor(variables are LP (ist price in dollars), LA (living area of the home in square feet), and LOT (lot size in acres) lf exactly two predictor (x) variables are to be used to predict the selling price, which two variables should be chosen? why? Click the icon to view the various regression equations. Choose the correct answer below. 0 A. 0 O C. 0 D. The best two explanatory variables are LP and LOT because their associated regression equation has the lowest P-value of 0.000 and the highest adjusted R2 of 0.989 The best to explanatory variables are LA and LOT because their associated regression equation has the highest P value of 0 000 and the lowest adjusted R2 of 0.779 The best two explanatory variables are LP and LA because their associated regression equation has the lowest P-value of 0.000 and a good adjusted R2 of 0 986 None of the combinations of two predictor variables can be used to predict the selling price. Data Table Predictor (x) Variables LP. LA, LOT LP, LA LP, LOT LA, LOT LP LA LOT P R2 Adjusted Regression Equation Value 0.000 0.000 0.987 0.000 0989 0.000 0.788 0.000 0.987 0.000 0.611 0.047 0.202 R2 0.986 0.986 0989 0.779 0.987 0.603 0.185 y=14.341+0.933 LP-0.7 LA+827 LOT y=12.372 + 0.958 LP-3.4 LA y=14.489 +0.928 LP +894 LOT y=114.042+99.7 LA+14,066 LOT y=12.305+0.939 LP y=137.327 + 102.0 LA y 322 927 15,031 LOT 0.987 0989 Click to select your answer

Explanation / Answer

Here, for this given problem we can answer the question by comparing the p-values and the adjusted R2 values.

Here, only two predictors are to be chosen and we can see that corresponding to the two predictors LP and LOT the p-value is around 0 which is less than 0.05 which implies that the two predictors significantly affect the response variable at 5% level of significance.

Also, the corresponding adjusted R2 value is 0.989 which is the maximum among all the R square values. It shows that the corresponding regression line of Y on the two predictors LP and LOT is very good fit.

So, we will choose LP and LOT as predictor variables.

Hence, answer (A) is correct.

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