A statistical program is recommended. Spring is a peak time for selling houses. Suppose the data below contains the selling price, number of bathrooms, square footage, and number of bedrooms of 26 homes sald in Ft. Thomas, Kentucky, in spring 2018. Selling Price Baths Sq Ft Beds Selling Price Sq Ft Baths Beds 160,000 1.5 1,786 3 295,000 2.5 1,860 3 170,000 2 1,768 3 325,000 3 2,056 4 178,000 1 1,219 325,000 3.5 2,776 4 182,500 1,578 328,400 2 1,408 4 195,100 1.5 1,125 331,000 1.5 1,972 3 212,500 2 1,196 2 344,500 2.5 1,736 3 245,900 2 2,128 3 365,000 2.5 1,990 4 250,000 3 1,280 3 385,000 2.5 3,640 4 255,000 1,596 3 395,000 2.5 1,908 4 258,000 3.5 2,374 4 399,000 2 2,108 3 267,000 2.5 2,439 3 430,000 2 2,462 4 268,000 2 1,470 4 430,000 2,615 4 275,000 2 1,668 4 454,000 3.5 3,700 4 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, x, denotes number of bedrooms, and y denotes the selling price.) 9 = -6111.69 + -1231.93x, + 59.93x, + 55071.38x, (a) Does the estimated regression equation provide a good fit to the data? Explain. (Round your answer to two decimal places.) Since the adjusted R2 = the estimated regression equation -Select-- v a good fit.

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