The trend in home building in recent years has been to emphasize open spaces and great rooms, rather than smaller living rooms and family rooms. A builder of speculative homes in the college community of Oxford, Ohio, had been building such homes, but his homes had been taking many months to sell and had been selling for substantially less than the asking price. In order to determine what types of homes would attract residents of the community, the builder contacted a statistician at a local college. The statistician went to a local real estate agency and obtained the data contained in file OxHome. This data includes the sales price (measured in thousand dollars), square footage, number of rooms, number of bedrooms, and age for each of 60 single-family residences recently sold in the community. Using this data, a regression model was built to predict the sales price of houses in this community. The regression equation from the model is: sales price (thousand dollars) = 19.5 + 0.1079 square feet + 11.88 rooms – 25.73 bedrooms – 0.721 age Given a 100 square feet increase in the size of the home, should you use it to include an additional bedroom, or keeping the number of rooms and bedrooms constant, should you use it to increase the size of the existing rooms to make more profit? A) Increase the size of the existing rooms B) Increase the number of bedrooms

Name: The trend in home building in recent years has been to emphasize open
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Description: The trend in home building in recent years has been to emphasize open spaces and great rooms, rather than smaller living rooms and family rooms. A builder of speculative homes in the college community of Oxford, Ohio, had been building such homes, bu

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

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The trend in home building in recent years has been to emphasize open spaces and great rooms, rather than smaller living rooms and family rooms. A builder of speculative homes in the college community of Oxford, Ohio, had been building such homes, but his homes had been taking many months to sell and had been selling for substantially less than the asking price. In order to determine what types of homes would attract residents of the community, the builder contacted a statistician at a local college. The statistician went to a local real estate agency and obtained the data contained in file OxHome. This data includes the sales price (measured in thousand dollars), square footage, number of rooms, number of bedrooms, and age for each of 60 single-family residences recently sold in the community.

Using this data, a regression model was built to predict the sales price of houses in this community. The regression equation from the model is:

sales price (thousand dollars) = 19.5 + 0.1079 square feet + 11.88 rooms – 25.73 bedrooms – 0.721 age

Given a 100 square feet increase in the size of the home, should you use it to include an additional bedroom, or keeping the number of rooms and bedrooms constant, should you use it to increase the size of the existing rooms to make more profit?

A) Increase the size of the existing rooms

B) Increase the number of bedrooms

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