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TABLE 13-6 One of the Most Common Questions of Prospective House Buyers

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TABLE 13-6
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 four 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 Microsoft Excel outputs of two regression models.
TABLE 13-6 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 four 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 Microsoft Excel outputs of two regression models.        -Referring to Table 13-6, the estimated value of the partial regression parameter β₁ in Model 1 means that A)  holding the effect of the other independent variables constant, an estimated expected $1 increase in heating costs is associated with a decrease in the daily minimum outside temperature by 4.51 degrees. B)  holding the effect of the other independent variables constant, a 1 degree increase in the daily minimum outside temperature results in a decrease in heating costs by $4.51. C)  holding the effect of the other independent variables constant, a 1 degree increase in the daily minimum outside temperature results in an estimated decrease in mean heating costs by $4.51. D)  holding the effect of the other independent variables constant, a 1% increase in the daily minimum outside temperature results in an estimated decrease in mean heating costs by 4.51%.
TABLE 13-6 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 four 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 Microsoft Excel outputs of two regression models.        -Referring to Table 13-6, the estimated value of the partial regression parameter β₁ in Model 1 means that A)  holding the effect of the other independent variables constant, an estimated expected $1 increase in heating costs is associated with a decrease in the daily minimum outside temperature by 4.51 degrees. B)  holding the effect of the other independent variables constant, a 1 degree increase in the daily minimum outside temperature results in a decrease in heating costs by $4.51. C)  holding the effect of the other independent variables constant, a 1 degree increase in the daily minimum outside temperature results in an estimated decrease in mean heating costs by $4.51. D)  holding the effect of the other independent variables constant, a 1% increase in the daily minimum outside temperature results in an estimated decrease in mean heating costs by 4.51%.
-Referring to Table 13-6, the estimated value of the partial regression parameter β₁ in Model 1 means that


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Capillary Refill

The time taken for color to return to an external capillary bed after pressure is applied; a measure of peripheral perfusion and circulatory status.

Pressure Injury

Damage to the skin and underlying tissue caused by prolonged pressure, often occurring in bed-ridden or immobilized individuals.

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