A home is for sale with a list price of $400,000, it has a living area of 3000 square feet, and it is on a 2 acre lot. What is the best predicted value of the selling price? Is that predicted selling price likely to be a good estimate? Is that predicted value likely to be very accurate?

Refer to the accompanying table, which was obtained using data from homes sold (from Data Set 23 in Appendix B). 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).

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Predictor (x) Variables LP, LA, Lot LP, LA LP, LOT LA, LOT LP LA LOT Adjusted R² 0.989 P-value R² 0.000 0.990 0.000 0.990 0.000 0.990 0.989 0.000 0.815 0.805 0.000 0.990 0.990 0.000 0.643 0.003 0.215 Regression Equation 1120+ 0.972 LP + 0.281 LA + 465 LOT 0.989-40.5 +0.985 LP 0.985 LA 0.633 0.194 = = = = = 1004 + 0.974 LP + 429 LOT 111,309 + 98.2 LA + 17,269 LOT 99.2 + 0.979 LP 133,936 + 101 LA 310,191 +19,217 LOT Data Set 23: Home Sales Homes Sold in Dutchess County, New York STATDISK: Minitab: Excel: TI-83/84 Plus: Text file names: 400000 414000 370000 379000 382500 389900 300000 299900 305000 319900 320000 319900 321000 328900 Selling List Price Price (dollars) (dollars) (sq. ft.) 445000 450000 377500 385000 460000 479000 265000 275000 299000 299000 385000 379000 430000 435000 214900 219900 475000 485000 280000 289000 457000 499900 210000 224900 272500 274900 268000 275000 300000 319900 477000 479000 292000 294900 379000 383900 295000 299900 499000 499000 292000 299000 305000 299900 520000 529700 308000 320000 Data set name is Homes. Worksheet name is HOMES.MTW. Workbook name is HOMES.XLS. App name is HOMES, and the file names are the same as for text files. 316000 310000 355500 362500 225000 229000 270000 290000 253000 259900 310000 314900 300000 309900 295000 295000 478000 479000 Text file names are HMSP, HMLST, HMLA, HMACR, HMAGE, HMTAX, HMRMS, HMBRS, HMBTH. Living Area 2704 2096 2737 1800 1066 1820 2700 2316 2448 3040 1500 1448 2400 2200 1635 2224 1738 3432 1175 1393 1196 1860 3867 1800 2722 2240 2174 1650 2000 3350 1776 1850 2600 1300 1352 1312 1664 1700 1650 2400 Acres 2.27 0.75 1.00 0.43 3.60 1.70 0.81 2.00 1.50 1.09 1.60 0.42 0.89 4.79 0.25 11.58 0.46 1.84 0.94 1.39 0.83 0.57 1.10 0.52 1.00 0.90 5.98 2.93 0.33 1.53 0.63 2.00 0.44 0.62 0.68 0.68 1.69 0.83 2.90 2.14 Age (years) 27 21 36 34 69 34 35 19 40 0 20 3947364921914444321229462526622546492443346 Taxes (dollars) 4920 4113 6072 4024 3562 4672 3645 6256 5469 6740 4046 3481 4411 5714 2560 7885 3011 9809 1367 2317 3360 4294 9135 3690 6283 3286 3894 3476 4146 8350 4584 4380 4009 3047 2801 4048 2940 4281 4299 6688 Rooms 888867899995678=O66668600 10 11 4 10 10 11 10 Bedrooms 3 ANAWNWWGWA AWWWWANAWNWWAWWWAAWNAAAWWWAAAW 4 4 4 4 4 4 Baths (full) 3 M N N N N N N N N N-3~-~~M-INTIMINIM ~ ~ ~ ~--~~~~ 2 2 2 2 2 1 2 3 2 2 1 2 1 2 1 1 1 2 4 1 1 2 1 2 2 2 2 1 1 1 2 2 2 2