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

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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 partial F test for H<sub>0</sub> : Variable X<sub>1</sub> does not significantly improve the model after variable X<sub>2</sub> has been included H<sub>1</sub> : Variable X<sub>1</sub> significantly improves the model after variable X<sub>2</sub> has been included has _____ and _____ degrees of freedom.
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 partial F test for H<sub>0</sub> : Variable X<sub>1</sub> does not significantly improve the model after variable X<sub>2</sub> has been included H<sub>1</sub> : Variable X<sub>1</sub> significantly improves the model after variable X<sub>2</sub> has been included has _____ and _____ degrees of freedom.
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 partial F test for H<sub>0</sub> : Variable X<sub>1</sub> does not significantly improve the model after variable X<sub>2</sub> has been included H<sub>1</sub> : Variable X<sub>1</sub> significantly improves the model after variable X<sub>2</sub> has been included has _____ and _____ degrees of freedom.
Also SSR (X1 | X2) = 8343.3572 and SSR (X2 | X1) = 4199.2672
-Referring to Scenario 14-6,the partial F test for
H0 : Variable X1 does not significantly improve the model after variable X2 has been included
H1 : Variable X1 significantly improves the model after variable X2 has been included has _____ and _____ degrees of freedom.


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