Applied Statistics Analysis of Variance and Regression [Paperback]

This work has been thoughtfully designed so that it serves equally well as a reference for the practitioner and as a self-contained textbook for the advanced student.
* Rewritten to maintain clarity and brevity while expanding the coverage of previous editions.
* Changes to design-related topics include increased discussion of mixed models and random effects, greater emphasis on regression and data screening, and more use of graphs throughout.
* Includes both graded and challenging exercises.
* Liberal computer discussions now supplemented with SAS and SPSS.Preface.

1. Data Screening.

1.1 Variables and Their Classification.

1.2 Describing the Data.

1.3 Departures from Assumptions.

1.4 Summary.

2. One-Way Analysis of Variance Design.

2.1 One-Way Analysis of Variance with Fixed Effects.

2.2 One-Way Analysis of Variance with Random Effects.

2.3 Designing an Observational Study or Experiment.

2.4 Checking if the Data Fit the One-Way ANOVA Model.

2.5 What to Do if the Data Do Not Fit the Model.

2.6 Presentation and Interpretation of Results.

2.7 Summary.

3. Estimation and Simultaneous Inference.

3.1 Estimation for Single Population Means.

3.2 Estimation for Linear Combinations of Population Means.

3.3 Simultaneous Statistical Inference.

3.4 Inference for Variance Components.

3.5 Presentation and Interpretation of Results.

3.6 Summary.

4. Hierarchical or Nested Design.

4.1 Example.

4.2 The Model.

4.3 Analysis of Varianclã(