A First Course in the Design of Experiments

A Linear Models Approach

John H. Skillings, Donald Weber

• Publisher: Routledge
• Year: 2018
• Topic: Mathematics
• eBook ISBN:
  9781351469968
• Subtopic: Probability & Statistics
• Index: Mathematics

Most texts on experimental design fall into one of two distinct categories. There are theoretical works with few applications and minimal discussion on design, and there are methods books with limited or no discussion of the underlying theory. Furthermore, most of these tend to either treat the analysis of each design separately with little attempt to unify procedures, or they will integrate the analysis for the designs into one general technique. A First Course in the Design of Experiments: A Linear Models Approach stands apart. It presents theory and methods, emphasizes both the design selection for an experiment and the analysis of data, and integrates the analysis for the various designs with the general theory for linear models. The authors begin with a general introduction then lead students through the theoretical results, the various design models, and the analytical concepts that will enable them to analyze virtually any design. Rife with examples and exercises, the text also encourages using computers to analyze data. The authors use the SAS software package throughout the book, but also demonstrate how any regression program can be used for analysis. With its balanced presentation of theory, methods, and applications and its highly readable style, A First Course in the Design of Experiments proves ideal as a text for a beginning graduate or upper-level undergraduate course in the design and analysis of experiments.

Table of contents

• Cover
• Half Title
• Title Page
• Copyright Page
• Table of Contents
• Chapter 1. Introduction to the Design of Experiments
• Chapter 2. Linear Models
• Chapter 3. Least Squares Estimation and Normal Equations
• Chapter 4. Linear Model Distribution Theory
• Chapter 5. Distribution Theory for Statistical Inference
• Chapter 6. Inference for Multiple Regression Models
• Chapter 7. The Completely Randomized Design
• Chapter 8. Planned Comparisons
• Chapter 9. Multiple Comparisons
• Chapter 10. Randomized Complete Block Design
• Chapter 11. Incomplete Block Designs
• Chapter 12. Latin Square Designs
• Chapter 13. Factorial Experiments with Two Factors
• Chapter 14. Other Factorial Experiments
• Chapter 15. Analysis of Covariance
• Chapter 16. Random and Mixed Models
• Chapter 17. Nested Designs and Associated Topics
• Chapter 18. Other Designs and Topics
• Appendix A Matrix Algebra
• Appendix B Tables
• References
• Solutions for Selected Odd-Numbered Exercises
• Index