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Instruction 13.32 One of the Most Common Questions of Prospective House Buyers

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Instruction 13.32
One of the most common questions of prospective house buyers pertains to the average cost of heating in dollars (Y) .
To provide its customers with information on that matter, a large real estate firm used the following four variables to predict heating costs: the daily minimum outside temperature in degrees of Celsius (X1) , the amount of insulation in cm (X2) , the number of windows in the house (X3) and the age of the furnace in years (X4) . Given below are the Microsoft Excel outputs of two regression models.
Instruction 13.32 One of the most common questions of prospective house buyers pertains to the average cost of heating in dollars (Y) . To provide its customers with information on that matter, a large real estate firm used the following four variables to predict heating costs: the daily minimum outside temperature in degrees of Celsius (X<sub>1</sub>) , the amount of insulation in cm (X<sub>2</sub>) , the number of windows in the house (X<sub>3</sub>)  and the age of the furnace in years (X<sub>4</sub>) . Given below are the Microsoft Excel outputs of two regression models.      -Referring to Instruction 13.32,what is your decision and conclusion for the test H<sub>0</sub>: β<sub>2</sub> = 0 vs.H<sub>1</sub>: β<sub>2</sub> < 0 at the α = 0.01 level of significance using Model 1? A)  Reject H<sub>0 </sub>and conclude that the amount of insulation does not have a linear effect on heating costs. B)  Reject H<sub>0 </sub>and conclude that the amount of insulation has a negative linear effect on heating costs. C)  Do not reject H<sub>0 </sub>and conclude that the amount of insulation has a linear effect on heating cots. D)  Do not reject H<sub>0 </sub>and conclude that the amount of insulation has a negative linear effect on heating costs. Instruction 13.32 One of the most common questions of prospective house buyers pertains to the average cost of heating in dollars (Y) . To provide its customers with information on that matter, a large real estate firm used the following four variables to predict heating costs: the daily minimum outside temperature in degrees of Celsius (X<sub>1</sub>) , the amount of insulation in cm (X<sub>2</sub>) , the number of windows in the house (X<sub>3</sub>)  and the age of the furnace in years (X<sub>4</sub>) . Given below are the Microsoft Excel outputs of two regression models.      -Referring to Instruction 13.32,what is your decision and conclusion for the test H<sub>0</sub>: β<sub>2</sub> = 0 vs.H<sub>1</sub>: β<sub>2</sub> < 0 at the α = 0.01 level of significance using Model 1? A)  Reject H<sub>0 </sub>and conclude that the amount of insulation does not have a linear effect on heating costs. B)  Reject H<sub>0 </sub>and conclude that the amount of insulation has a negative linear effect on heating costs. C)  Do not reject H<sub>0 </sub>and conclude that the amount of insulation has a linear effect on heating cots. D)  Do not reject H<sub>0 </sub>and conclude that the amount of insulation has a negative linear effect on heating costs.
-Referring to Instruction 13.32,what is your decision and conclusion for the test H0: β2 = 0 vs.H1: β2 < 0 at the α = 0.01 level of significance using Model 1?


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