Stressing central concepts such as model building, understanding parameters, assessing fit and reliability, and drawing conclusions, the new edition illustrates how to develop estimation, confidence, and testing procedures primarily through the use of least squares regression. While maintaining the accessible appeal of each previous edition,Applied Linear Regression, Fourth Edition features:
- Graphical methods stressed in the initial exploratory phase, analysis phase, and summarization phase of an analysis
- In-depth coverage of parameter estimates in both simple and complex models, transformations, and regression diagnostics
- Newly added material on topics including testing, ANOVA, and variance assumptions
- Updated methodology, such as bootstrapping, cross-validation binomial and Poisson regression, and modern model selection methods
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