Design and Analysis of Experiments

Design and Analysis of Experiments emphasizes the practical considerations governing the design of an experiment based on the objectives of the study and a solid statistical foundation for the analysis. Almost all data sets in the book have been obtained from real experiments, either run by students in statistics and the applied sciences, or published in the scientific literature. Details of the planning stage of numerous different experiments are discussed. The statistical analysis of experimental data is based on estimable functions and is developed with some care.

Design and Analysis of Experiments starts with basic principles and techniques of experimental design and analysis of experiments. It provides a checklist for the planning of experiments, and explains the estimation of treatment contrasts and analysis of variance. These basics are then applied in a wide variety of settings. Designs covered include completely randomized designs, complete and incomplete block designs, row-column designs, single replicate designs with confounding, fractional factorial designs, response surface designs, and designs involving nested factors and factors with random effects, including split-plot designs.

The book is accessible to all readers who have a good basic knowledge of expected values, confidence intervals and hypothesis tests. It is ideal for use in the classroom at both the senior undergraduate and the graduate level. A guide to the use of the SAS System computer package is given at the end of each chapter, but the book can equally well be used in conjunction with any statistical package. Exercises based on a large number of different experiments are included in most chapters.

Contents

• Principles and Techniques
• Planning Experiments
• Designs With One Source of Variation
• Inferences for Contrasts and Treatment Means
• Checking Model Assumptions
• Experiments With Two Crossed Treatment Factors
• Several Crossed Treatment Factors
• Polynomial Regression
• Analysis of Covariance
• Complete Block Designs
• Incomplete Block Designs
• Designs With Two Blocking Factors
• Confounded Two-Level Factorial Experiments
• Confounding in General Factorial Experiments
• Fractional Factorial Experiments
• Response Surface Methodology
• Random Effects and Variance Components
• Nested Models
• Split-Plot Designs