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Question
NARRBEGIN: SA_94_99A local truck rental company wants to use regression to predict the yearly maintenance expense (Y), in dollars, for a truck using the number of miles driven during the year
and the age of the truck in years 
at the beginning of the year. To examine the relationship, the company has gathered the data on 15 trucks and regression analysis has been conducted. The regression output is presented below.| Summary measures | |
| Multiple R | 0.9308 |
| R-Square | 0.8665 |
| Adj R-Square | 0.8442 |
| StErr of Estimate | 87.397 |
| ANOVA Table | |||||
| Source | df | SS | MS | F | p-value |
| Explained | 2 | 594690 | 297345 | 38.9287 | 0.0000 |
| Unexplained | 12 | 91658 | 7638 | ||
| Regression coefficients | |||||
| Coefficient | Std Err | t-value | p-value | ||
| Constant | -680.70 | 161.27 | -4.2210 | 0.0012 | |
| Miles Driven | 0.080 | 0.015 | 5.1831 | 0.0002 | |
| Age of Truck | 44.238 | 10.444 | 4.2359 | 0.0012 | |
(A) Estimate the regression model. How well does this model fit the given data?
(B) Is there a linear relationship between the two explanatory variables and the dependent variable at the 5% significance level? Explain how you arrived at your answer.
(C) Use the estimated regression model to predict the annual maintenance expense of a truck that is driven 14,000 miles per year and is 5 years old.
(D) Find a 95% prediction interval for the maintenance expense determined in (C). Use a t-multiple = 2.
(E) Find a 95% confidence interval for the maintenance expense for all trucks sharing the characteristics provided in Question 96. Use a t-multiple = 2.
(F) How do you explain the differences between the widths of the intervals in (D) and (E)?
Answer
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