14. Figure A contains the selling price and area (in square feet) of 60 recently sold homes in a region where a buyer wants to purchase a home, as well as the regression line for these data. Figure B gives a prediction, a prediction interval, and a confidence interval for a home with 2500 square feet. Complete parts a through d. 1 Click the icon to view Figures A and B. a. Use the equation to estimate the price of a home with 2500 square feet. $ (Round to the nearest integer as needed.) b. The buyer wants to know the uncertainty in the prices he might pay for a home with 2500 square feet in this region. Should he use a prediction interval or a confidence interval? Explain. O A. He should use a confidence interval because he wants to predict the value for one home, not for the mean of a group of homes. O B. He should use a confidence interval because he wants to predict the value of the mean of a group of homes, not for one home. O C. He should use a prediction interval because he wants to predict the value for one home, not for the mean of a group of homes. O D. He should use a prediction interval because he wants to predict the value of the mean of a group of homes, not for one home. c. Report the correct 95% interval, confidence or prediction, as determined in part b, for the predicted price. See Figure B. d. The buyer has prequalified for a loan up to $380,000. Is he likely to be able to afford a house in this area with 2500 square feet? O A. No, because the amount of the loan is contained in the 95% interval O B. Yes, because the amount of the loan is greater than the upper bound of the 95% interval O C. No, because the amount of the loan is less than the midpoint of the 95% interval O D. No, because the amount of the loan is greater than the upper bound of the 95% interval O E. Yes, because the amount of the loan is greater than the midpoint of the 95% interval OF. Yes, because the amount of the loan is contained in the 95% interval Screenshot 2023-04-12 at 6.... . Q Q 2 . ' Q Search 1: Scatterplot and Technology Output (A) Price = 38698 + 92.6 Area 500,000- 400,000- 300,000- Price ( 200,000- 100,000. 0- 500 1,500 2,500 3,500 Area (square feet) (B) Predicted Values For New Observations New Obs Fit SE Fit 95% CI 95% PI 270089 5970 (258138, 282039) (194788, 345390) Values of Predictors for New Observations New Obs Area 2500