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 coefficientsConstruct Type: 1-brick 2-brick and frame 3-aluminum and frame 4-frame Style: 1-two story 2-one and half story 3-ranch

C D G H K L M N Taxes Number of Bathrooms Lot size House size Number of garages Number of rooms Number of bedrooms Age of the home Construction type Style Number of fireplaces Sale Price 491 76 3472 998 42 0 25900 502.08 3531 1500 62 29500 454 29 2275 1175 40 27900 455.73 4050 1232 54 25900 505.97 4455 1121 42 29900 NOOO 389.1 1 4455 988 29900 589.8 5850 1240 30900 560.39 1 9520 1501 28900 1642 02 2. 9800 3420 84900 1445.98 2.5 12800 3000 82900 582.82 6435 1225 35900 530.03 4988 3 1552 31500 627.12 $520 975 31000 595.92 1 HOOD 6666 1121 30900 505 1 5000 1020 30000 560.39 9520 1501 28900 824.64 1.5 5150 1664 36900 669.69 1.5 6902 1488 i N 41900 20 778.41 1.5 7102 1376 HOOKO 40500 903.84 1 7800 1500 43900 598.94 1 5520 1256 37500 754.22 1.5 4000 1690 37900 879.51 1.5 9890 1820 44500 609.31 1.5 6726.5 1652 37900 26 836.07 1.5 9150 1777 38900 814 8000 1504 36900 28 914. 16 1.5 7326.2 1831 45800 29 1200 1.5 5000 1200 30 41000 30 31 32 33 Construction Type