9.2.3 Exploration 9B: Maintenance Cost for Trucks
The data file C09 Truck data.xls [.rda] contains information on trucks owned by Metro Area
Trucking. We are interested in predicting how all of the variables influence the maintenance
costs.
- Analyze the Variables
- What variable would be the response variable?
- Which of the explanatory variables are numerical? What are their units?
- Which explanatory variables are categorical? What are the possible categories for
each?
- What dummy variables need to be created? (Notice that ”location” is already
coded as 0 or 1, so there is no need to create dummy variables for it.)
- Build the models
- Create the full regression model. What is the equation of the model? How good
is this model? What does it tell you about maintenance costs for each type of
truck? How does location influence the maintenance cost?
- Are there any variables in the full model that should be eliminated? Why? Is
there a theoretical justification for eliminating them?
- Create a model with nonessential variables eliminated. What is the model
equation? How does it compare (in quality) with the full regression model? What
does it tell you about the maintenance costs of each type of truck? What does
this model tell you about how location affects maintenance costs?