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SCENARIO 18-2 One of the Most Common Questions of Prospective

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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 ( 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 ( ) , the amount of insulation in inches ( ) , the number of windows in the house ( ) , and the age of the furnace in years ( ) .Given below are the EXCEL outputs of two regression models. -Referring to Scenario 18-2 and allowing for a 1% probability of committing a type I error, what is the decision and conclusion for the test j =1, 2,..., 4 using Model 1? A) Do not reject and conclude that the 4 independent variables have significant individual linear effects on heating costs. B) Reject and conclude that the 4 independent variables taken as a group have significant linear effects on heating costs. C) Do not reject and conclude that the 4 independent variables taken as a group do not have significant linear effects on heating costs. D) Reject and conclude that the 4 independent variables taken as a group do not have significant linear effects on heating costs. ) , the amount of insulation in inches ( 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 ( ) , the amount of insulation in inches ( ) , the number of windows in the house ( ) , and the age of the furnace in years ( ) .Given below are the EXCEL outputs of two regression models. -Referring to Scenario 18-2 and allowing for a 1% probability of committing a type I error, what is the decision and conclusion for the test j =1, 2,..., 4 using Model 1? A) Do not reject and conclude that the 4 independent variables have significant individual linear effects on heating costs. B) Reject and conclude that the 4 independent variables taken as a group have significant linear effects on heating costs. C) Do not reject and conclude that the 4 independent variables taken as a group do not have significant linear effects on heating costs. D) Reject and conclude that the 4 independent variables taken as a group do not have significant linear effects on heating costs. ) , the number of windows in the house ( 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 ( ) , the amount of insulation in inches ( ) , the number of windows in the house ( ) , and the age of the furnace in years ( ) .Given below are the EXCEL outputs of two regression models. -Referring to Scenario 18-2 and allowing for a 1% probability of committing a type I error, what is the decision and conclusion for the test j =1, 2,..., 4 using Model 1? A) Do not reject and conclude that the 4 independent variables have significant individual linear effects on heating costs. B) Reject and conclude that the 4 independent variables taken as a group have significant linear effects on heating costs. C) Do not reject and conclude that the 4 independent variables taken as a group do not have significant linear effects on heating costs. D) Reject and conclude that the 4 independent variables taken as a group do not have significant linear effects on heating costs. ) , and the age of the furnace in years ( 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 ( ) , the amount of insulation in inches ( ) , the number of windows in the house ( ) , and the age of the furnace in years ( ) .Given below are the EXCEL outputs of two regression models. -Referring to Scenario 18-2 and allowing for a 1% probability of committing a type I error, what is the decision and conclusion for the test j =1, 2,..., 4 using Model 1? A) Do not reject and conclude that the 4 independent variables have significant individual linear effects on heating costs. B) Reject and conclude that the 4 independent variables taken as a group have significant linear effects on heating costs. C) Do not reject and conclude that the 4 independent variables taken as a group do not have significant linear effects on heating costs. D) Reject and conclude that the 4 independent variables taken as a group do not have significant linear effects on heating costs. ) .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 ( ) , the amount of insulation in inches ( ) , the number of windows in the house ( ) , and the age of the furnace in years ( ) .Given below are the EXCEL outputs of two regression models. -Referring to Scenario 18-2 and allowing for a 1% probability of committing a type I error, what is the decision and conclusion for the test j =1, 2,..., 4 using Model 1? A) Do not reject and conclude that the 4 independent variables have significant individual linear effects on heating costs. B) Reject and conclude that the 4 independent variables taken as a group have significant linear effects on heating costs. C) Do not reject and conclude that the 4 independent variables taken as a group do not have significant linear effects on heating costs. D) Reject and conclude that the 4 independent variables taken as a group do not have significant linear effects on heating costs.
-Referring to Scenario 18-2 and allowing for a 1% probability of committing a type I error, what is the decision and conclusion for the test 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 ( ) , the amount of insulation in inches ( ) , the number of windows in the house ( ) , and the age of the furnace in years ( ) .Given below are the EXCEL outputs of two regression models. -Referring to Scenario 18-2 and allowing for a 1% probability of committing a type I error, what is the decision and conclusion for the test j =1, 2,..., 4 using Model 1? A) Do not reject and conclude that the 4 independent variables have significant individual linear effects on heating costs. B) Reject and conclude that the 4 independent variables taken as a group have significant linear effects on heating costs. C) Do not reject and conclude that the 4 independent variables taken as a group do not have significant linear effects on heating costs. D) Reject and conclude that the 4 independent variables taken as a group do not have significant linear effects on heating costs. j =1, 2,..., 4 using Model 1?

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