The writer is very fast, professional and responded to the review request fast also. Thank you.
Book/movie review
22/08/2022
TABLE 12-6
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 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
______________________________________
Regression Statistics
_______________________________________
R Square 0.8080
Adjusted R Square 0.7568
Observations 20
_______________________________________
ANOVA
__________________________________________________________________________
df SS MS F Significance F
__________________________________________________________________________
Regression 4(NNN) NNN-NNNN42375.86 15.7874 2.96869E-05
Residual 15NNN-NN-NNNN 2684.155
Total 19 209765.75
__________________________________________________________________________
__________________________________________________________________________
Coefficients Standard Error t Stat P-value Lower 90% Upper 90%
__________________________________________________________________________
Intercept (NNN) NNN-NNNN77.8614 5.4125 7.2E-05(NNN) NNN-NNNN557.9227
X1 (Temperature) -4.5098 0.8129 -5.5476 5.58E-05 -5.9349 -3.0847
X2 (Insulation) -14.9029 5.0508 -2.9505 0.0099 -23.7573 -6.0485
X3 (Windows) 0.2151 4.8675 0.0442 0.9653 -8.3181 8.7484
X4 (Furnace Age) 6.3780 4.1026 1.5546 0.1408 -0.8140 13.5702
__________________________________________________________________________
Model 2
___________________________________
Regression Statistics
___________________________________
R Square 0.7768
Adjusted R Square 0.7506
Observations 20
___________________________________
ANOVA
__________________________________________________________________________
df SS MS F Significance F
__________________________________________________________________________
Regression 2(NNN) NNN-NNNN81479.11 29.5923 2.9036E-06
Residual 17NNN-NN-NNNN 2753.384
Total 19 209765.75
__________________________________________________________________________
__________________________________________________________________________
Coefficients Standard Error t Stat P-value Lower 95% Upper 95%
__________________________________________________________________________
Intercept (NNN) NNN-NNNN 43.9826 11.1253 3.17E-09(NNN) NNN-NNNN582.1180
X1 (Temperature) -5.1103 0.6951 -7.3515 1.13E-06 -6.5769 -3.6437
X2 (Insulation) -14.7195 4.8864 -3.0123 0.0078 -25.0290 -4.4099
__________________________________________________________________________
19. Referring to Table 12-6, the estimated value of the partial regression parameter B1 in Model 1 means that:
a. all else equal, an estimated expected $1 increase in average heating costs is associated with a decrease in the daily minimum outside temperature by 4.51 degrees.
b. all else equal, a 1 degree increase in the daily minimum outside temperature results in a decrease in average heating costs by $4.51.
c. all else equal, a 1 degree increase in the daily minimum outside temperature results in an estimated expected decrease in average heating costs by $4.51.
d. all else equal, a 1% increase in the daily minimum outside temperature results in an estimated expected decrease in average heating costs by 4.51%.
20. Referring to Table 12-6, what is the 90% confidence interval for the expected change in average heating costs as a result of a 1 degree Fahrenheit change in the daily minimum outside temperature using Model 1?
a. [-6.58, -3.65]
b. [-6.24, -2.78]
c. [-5.94, -3.08]
d. [-2.37, 15.12]
The writer is very fast, professional and responded to the review request fast also. Thank you.
Delivering a high-quality product at a reasonable price is not enough anymore.
That’s why we have developed 5 beneficial guarantees that will make your experience with our service enjoyable, easy, and safe.
You have to be 100% sure of the quality of your product to give a money-back guarantee. This describes us perfectly. Make sure that this guarantee is totally transparent.
Read moreEach paper is composed from scratch, according to your instructions. It is then checked by our plagiarism-detection software. There is no gap where plagiarism could squeeze in.
Read moreThanks to our free revisions, there is no way for you to be unsatisfied. We will work on your paper until you are completely happy with the result.
Read moreYour email is safe, as we store it according to international data protection rules. Your bank details are secure, as we use only reliable payment systems.
Read moreBy sending us your money, you buy the service we provide. Check out our terms and conditions if you prefer business talks to be laid out in official language.
Read more