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SCENARIO 14-6
One of the Most Common Questions of Prospective β\beta

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SCENARIO 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 ( X 2 ) . Given below is EXCEL output of the regression model.
 SCENARIO 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 Scenario 14-6,the estimated value of the regression parameter  \beta <sub>1 </sub>in 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%.
 SCENARIO 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 Scenario 14-6,the estimated value of the regression parameter  \beta <sub>1 </sub>in 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%.
 SCENARIO 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 Scenario 14-6,the estimated value of the regression parameter  \beta <sub>1 </sub>in 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 Scenario 14-6,the estimated value of the regression parameter β\beta 1 in means that


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