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TABLE 14-6 One of the Most Common Questions of Prospective House Buyers

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TABLE 14-6
One of the most common questions of prospective house buyers pertains to the cost of heating in dollars (Y) .To provide its customers with information on that matter,a large real estate firm used the following 2 variables to predict heating costs: the daily minimum outside temperature in degrees of Fahrenheit (X1) and the amount of insulation in inches (X2) .Given below is EXCEL output of the regression model. TABLE 14-6 One of the most common questions of prospective house buyers pertains to the cost of heating in dollars (Y) .To provide its customers with information on that matter,a large real estate firm used the following 2 variables to predict heating costs: the daily minimum outside temperature in degrees of Fahrenheit (X<sub>1</sub>) and the amount of insulation in inches (X<sub>2</sub>) .Given below is EXCEL output of the regression model.   Also SSR (X<sub>1</sub> ∣ X<sub>2</sub>) = 8343.3572 and SSR (X<sub>2</sub> ∣ X<sub>1</sub>) = 4199.2672 -Referring to Table 14-6,the estimated value of the regression parameter β<sub>1</sub> means that A) holding the effect of the amount of insulation constant,an estimated expected $1 increase in heating costs is associated with a decrease in the daily minimum outside temperature by 2.76 degrees. B) holding the effect of the amount of insulation constant,a 1 degree increase in the daily minimum outside temperature results in a decrease in heating costs by $2.76. C) holding the effect of the amount of insulation constant,a 1 degree increase in the daily minimum outside temperature results in an estimated decrease in mean heating costs by $2.76. D) holding the effect of the amount of insulation constant,a 1% increase in the daily minimum outside temperature results in an estimated decrease in mean heating costs by 2.76%. Also SSR (X1 ∣ X2) = 8343.3572 and SSR (X2 ∣ X1) = 4199.2672
-Referring to Table 14-6,the estimated value of the regression parameter β1 means that


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