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# In a study of Housing Demand, the country assessor is interested in developing a regression model to estimate the

market value (i.e, selling price) of residential property within his jurisdiction. He randomly selected 15 houses as shown in the table below: (Total Marks: 20 Marks) Observation Selling Price(x\$1000) Size(x\$100 ft2) Total No. Of Rooms Age Attached Garage (No=0,Yes=1) 1 65.2 12.0 6 17 0 2 79.6 20.2 7 18 0 3 111.2 27.0 7 17 1 4 128.0 30.0 8 18 1 5 152.0 30.0 8 15 1 6 81.2 21.4 8 20 1 7 88.5 21.6 7 8 0 8 92.8 25.2 7 15 1 9 156.0 37.2 9 31 1 10 63.2 14.4 7 8 0 11 72.4 15.0 7 17 0 12 91.2 22.4 6 9 0 13 99.6 23.9 7 20 1 14 107.6 26.6 6 23 1 15 120.4 30.7 7 23 1 QUESTIONS a. Determine the estimated regression equation with the four explanatory variables shown in the table. b. Give an interpretation of each of the regression coefficients. c. What proportion of the total variation in Selling Price is explained by the regression model? d. Briefly explain the independent variable of attached garage for any two observations and compare.

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