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SCENARIO 18-2
One of the Most Common Questions of Prospective β\beta

Question 253

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SCENARIO 18-2
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 4 variables to predict heating costs: the daily minimum outside temperature in degrees of Fahrenheit ( X1 ) , the amount of insulation in inches ( X 2 ) , the number of windows in the house ( X3 ) , and the age of the furnace in years ( X 4 ) . Given below are the EXCEL outputs of two regression models.
SCENARIO 18-2 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 4 variables to predict heating costs: the daily minimum outside temperature in degrees of Fahrenheit ( X<sub>1</sub> ) , the amount of insulation in inches ( 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 EXCEL outputs of two regression models. -Referring to Scenario 18-2,what is your decision and conclusion for the test H<sub>0 </sub>: \beta <sub>2</sub> = 0 vs.H<sub>1 </sub>: \beta <sub>2</sub> \lt 0 at the \alpha = 0.01 level of significance using Model 1 ? A) Do not reject H<sub>0</sub> and conclude that the amount of insulation has a linear effect on heating cots. B) Reject H<sub>0</sub> and conclude that the amount of insulation does not have a linear effect on heating costs. C) Reject H<sub>0</sub> and conclude that the amount of insulation has a negative linear effect on heating costs. D) Do not reject H<sub>0</sub> and conclude that the amount of insulation has a negative linear effect on heating costs.
SCENARIO 18-2 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 4 variables to predict heating costs: the daily minimum outside temperature in degrees of Fahrenheit ( X<sub>1</sub> ) , the amount of insulation in inches ( 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 EXCEL outputs of two regression models. -Referring to Scenario 18-2,what is your decision and conclusion for the test H<sub>0 </sub>: \beta <sub>2</sub> = 0 vs.H<sub>1 </sub>: \beta <sub>2</sub> \lt 0 at the \alpha = 0.01 level of significance using Model 1 ? A) Do not reject H<sub>0</sub> and conclude that the amount of insulation has a linear effect on heating cots. B) Reject H<sub>0</sub> and conclude that the amount of insulation does not have a linear effect on heating costs. C) Reject H<sub>0</sub> and conclude that the amount of insulation has a negative linear effect on heating costs. 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 Scenario 18-2,what is your decision and conclusion for the test H0 : β\beta 2 = 0 vs.H1 : β\beta 2 <\lt 0 at the α\alpha = 0.01 level of significance using Model 1 ?


A) Do not reject H0 and conclude that the amount of insulation has a linear effect on heating cots.
B) Reject H0 and conclude that the amount of insulation does not have a linear effect on heating costs.
C) Reject H0 and conclude that the amount of insulation has a negative linear effect on heating costs.
D) Do not reject H0 and conclude that the amount of insulation has a negative linear effect on heating costs.

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