File - Home Insert Page Layout Formulas Data Review B Sq Ft Beds Nm 5 Baths 1.5 2 1 1 1.5 2 2 3 2 3.5 2.5 2 2 2.5 3 3.5 2 1 Selling Price 2 160000 3 170000 4 178000 182500 6 195100 7 212500 8 245900 9 250000 10 255000 11 258000 12 267000 13 268000 14 275000 15 295000 16 325000 17 325000 328400 19 331000 20 344500 21 365000 22 385000 23 395000 24 399000 25 430000 26 430000 27 454000 28 3 3 3 3 2 3 2 3 3 3 4 3 4 4 3 4 4 4 1776 1768 1219 1568 1125 1196 2128 1280 1596 2374 2439 1470 1678 1860 2056 2776 1408 1972 1736 1990 3640 1918 2108 2462 2615 3700 2 2 3 3 2. 18 1.5 2.5 2.5 2.5 2.5 2 2 2 3 3 4 4 4 3 CICLE 4 Data Spring is a peak time for selling houses. The file Spring Houses contains the selling price, number of bathrooms, square footage, and number of bedrooms of 26 homes sold in it. Thomas, Kentucky, in spring 2018, Consider the estimated regression equation we developed that can be used to predict the selling price given the number of bathrooms, square footage, and number of bedrooms in the house. (x, denotes number of bathrooms, x, denotes square footage, xz denotes number of bedrooms, and y denotes the selling price) 8 = -5531.01 - 1386.21%, +60.28x54797.08x, (a) Does the estimated regression equation provide a good fit to the data? Explain. (Round your answer to two decimal places.) Since the adjusted R? the estimated regression equation Saled- a good (6) Consider the estimated regression equation that was developed which predicts selling price given the square footage and number of bedrooms (x, denotes square footage, denotes number of bedrooms, and y denotes the selling price) P = -5882.76 + 59.73x, +54309 21x7 Compare the fit for this simpler model to that of the model that also includes number of bathrooms as an independent variable. (Round your answer to two decimal places) The adjusted R for the simpler model is which is Select than the adjusted R in part (a). The model from part 2 is preferred