Chapter 10: Diagnostic Methods for Regression, Curve Fitting, and ANOVA

10.1 Introduction

10.2 Computing Residuals with Fit Y by X and Fit Model

10.2.1 Fit Y by X

10.2.2 Fit Model

10.3 Checking for Normality

10.4 Checking for Nonconstant Error Variance (Heteroscedasticity)

10.5 Checking for Outliers

10.6 Checking for Nonindependence

10.7 Multiple Factor Diagnostics

10.8 Nonlinear Fit Residuals

10.9 Developing Appropriate Models

10.10 References

10.1 Introduction

To examine the quality of a model and the appropriateness of a modeling method, it is necessary to examine residuals. Residuals are errors and can be described as the difference between the known and predicted values. Of particular interest are linear regression, discussed in Chapter ...

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