Ds 533 Fall 2004 Exam # 3
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Interpret each of the estimated regression coefficients of the regression model in Question a. For every extra 100 miles driven, the maintenance cost goes up by $5.49, given the age of the car is fixed. As the age of the car goes up by one year the maintenance cost goes up by $21.467, give the miles driven is fixed. Identify and interpret the coefficient of determination (  ), and the standard error of the estimate (Sy.x) for the model in Question 3.
R2 = .9387. 93.87% of the variability in maintenance cost can be explained by the age of the car and the miles driven. S = 72.218. This measures the variability around the fitted model. d. Does the given set of explanatory variables do a good job of explaining changes in the maintenance costs? Explain why or why not. The R2 is high, indicating a good model, but the variable age of the car is not a significant predictor of the maintenance car given the first variable (Miles driven) in the model. The variable age of the car may not be needed in the model. Would you recommend that this company examine any other factors to predict maintenance expense? If yes, what other factors would you want to consider? Explain your answer. This is a good model with R2 = 94%. Other variable that may be considered is the make and model of the car. Give a 95% confidence interval for the average yearly maintenance cost for an automobile for every extra mile driven during the year (  ).
g. What is the average yearly maintenance cost for a 10-year-old automobile that drives 12000 miles per year? Download 376.15 Kb. Share with your friends:
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