Using the dataset, build regression models to: 1) Predict sale price using house size (mean centered) and age of home 2) predict sale price using lot size (mean centered) and number of bathrooms (dummy coded: 1 bathroom vs more than 1 bathrooms) Interpret the significant coefficients

Number of Bathrooms Lot she House Size Number of gara Age of the home Construction type Style Number of fireplaces Sale Price 491. 76 3472 998 25900 3531 2500 29500 454.29 2275 1175 27900 455 73 8050 1232 25900 505 97 6455 1121 29900 8455 988 29900 5850 1240 30900 360.39 9520 1501 28900 1542 02 9809 3429 84900 1445.98 25 12800 3000 82900 582 82 5435 1225 35900 530 03 1552 31500 627 12 5520 975 31000 395 92 1121 30900 5009 1020 30000 560.39 9520 1501 28900! 824.64 15 3150 1654 36900 HO 869 59 6902 1488 41900 778.41 15 7102 1876 40500! 903 84 7800 1500 439001 598 94 8520 1256 37500, 754 27 4000 1690 37900 879.51 15 9890 1820 44500 609 31 8720.6 1652 OHONO 37900 836.07 9150 1779 38900! 814 8000 150 369001 28 914.16 1.5 73260 1831 O 45800 1200 15 5000 1200 30 41000 Construction Type 1. Brick 2. Brick and frame 3- Aluminum and frame 37 Sheet! Select destination and press ENTER or choose Paste