4. Process Modeling
4.6. Case Studies in Process Modeling

4.6.2.

Alaska Pipeline

Non-Homogeneous Variances

This example illustrates the construction of a linear regression model for Alaska pipeline ultrasonic calibration data. This case study demonstrates the use of transformations and weighted fits to deal with the violation of the assumption of constant standard deviations for the random errors. This assumption is also called homogeneous variances for the errors.

1. Background and Data
2. Check for a Batch Effect
3. Fit Initial Model
4. Transformations to Improve Fit and Equalize Variances
5. Weighting to Improve Fit
6. Compare the Fits
7. Work This Example Yourself