A statistical program is recommended. DATAfile: Spring Houses 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 Ft.TH 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 house. (x, denotes number of bathrooms, X, denotes square footage, X, denotes number of bedrooms, and y denotes the selling price.) = -5531.01 - 1386.21x, + 60.28x, +54797.08% (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 Select a good fit (b) Consider the estimated regression equation that was developed which predicts selling price given the square footage and number of bedrooms. (x, denotes square footage, X denotes number of bedrooms, and y denotes the selling price.) y = -5882.76 + 59.73, +54309.21% 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 Rin part(). The model from part ? is preferred. D Beds B Baths 15 2 A 1 Selling Pricel 160000 170000 178000 182500 195100 212500 245900 250000 255000 258000 267000 268000 275000 295000 325000 325000 328400 331000 344500 365000 385000 395000 is is NWN Nir C Sq Ft 1776 1768 1219 1568 1125 1196 2128 1280 1596 2374 2439 1470 1678 1860 2056 2776 1408 1972 1736 1990 3640 1918 ) 399000 430000 430000 45000 1918 2108 2462 2615 3700