Instruction 13.18 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 1 ), the amount of insulation in cm (X 2 ), the number of windows in the house (X 3 ) and the age of the furnace in years (X 4 ). Given below are the Microsoft Excel outputs of two regression models. -Referring to Instruction 13.18 and allowing for a 1% probability of committing a Type I error,what is the decision and conclusion for the test H₀: β₁ = β₂ = β₃ = β₄ = 0 vs.H₁: At least one β_j ≠ 0,j = 1,2,...,4 using Model 1? A) Reject H₀ and conclude that the four independent variables taken as a group do not have significant linear effects on heating costs. B) Do not reject H₀ and conclude that the four independent variables have significant individual linear effects on heating costs. C) Reject H₀ and conclude that the four independent variables taken as a group have significant linear effects on average heating costs. D) Do not reject H₀ and conclude that the four independent variables taken as a group do not have significant linear effects on heating costs.

Question

Quizplus · Accepted Answer

Based on Model 1, the F-statistic value for the overall significance of the regression model is 195.8 with a p-value of less than 0.01, which indicates that the model is significant as a whole. Therefore, we can reject H₀. Also, for each independent variable, the p-value is less than 0.01, which means that each variable has a significant linear effect on heating costs individually. Therefore, we can conclude that the four independent variables taken as a group have significant linear effects on average heating costs.

Instruction 13.18 One of the Most Common Questions of Prospective House Buyers