
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 can we say about Model 1?
A) The model explains 77.7% of the sample variability of heating costs; after correcting for the degrees of freedom, the model explains 75.1% of the sample variability of heating costs.
B) The model explains 75.1% of the sample variability of heating costs; after correcting for the degrees of freedom, the model explains 77.7% of the sample variability of heating costs.
C) The model explains 80.8% of the sample variability of heating costs; after correcting for the degrees of freedom, the model explains 75.7% of the sample variability of heating costs.
D) The model explains 75.7% of the sample variability of heating costs; after correcting for the degrees of freedom, the model explains 80.8% of the sample variability of heating costs.
Correct Answer:
Verified
Q64: TABLE 14-6
One of the most common questions
Q65: TABLE 14-5
A microeconomist wants to determine how
Q66: TABLE 14-5
A microeconomist wants to determine how
Q67: TABLE 14-5
A microeconomist wants to determine how
Q68: In calculating the standard error of the
Q70: TABLE 14-6
One of the most common questions
Q73: TABLE 14-6
One of the most common questions
Q74: When an additional explanatory variable is introduced
Q89: When an additional explanatory variable is introduced
Q94: When an explanatory variable is dropped from
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