Multiple Choice
TABLE 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 4 variables to predict heating costs: the daily minimum outside temperature in degrees of Fahrenheit (X₁) the amount of insulation in inches (X₂) , the number of windows in the house (X₃) , and the age of the furnace in years (X₄) . Given below are the Excel outputs of two regression models.
Model 1
Model 2
-Referring to Table 14-6, 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?
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.
Correct Answer:

Verified
Correct Answer:
Verified
Q244: TABLE 14-17<br> <img src="https://d2lvgg3v3hfg70.cloudfront.net/TB1602/.jpg" alt="TABLE 14-17
Q245: TABLE 14-18<br>A logistic regression model was estimated
Q246: TABLE 14-15<br>The superintendent of a school district
Q247: In a multiple regression model, the adjusted
Q248: TABLE 14-5<br>A microeconomist wants to determine how
Q250: TABLE 14-4<br>A real estate builder wishes to
Q251: TABLE 14-15<br>The superintendent of a school district
Q252: TABLE 14-15<br>The superintendent of a school district
Q253: When an explanatory variable is dropped from
Q254: TABLE 14-2<br>A professor of industrial relations believes