Design and Analysis of Experiments, Volume 1: Introduction to Experimental Design, 2nd Edition

Design and Analysis of Experiments, Volume 1, Second Edition provides a general introduction to the philosophy, theory, and practice of designing scientific comparative experiments and also details the intricacies that are often encountered throughout the design and analysis processes. With the addition of extensive numerical examples and expanded treatment of key concepts, this book further addresses the needs of practitioners and successfully provides a solid understanding of the relationship between the quality of experimental design and the validity of conclusions.

This Second Edition continues to provide the theoretical basis of the principles of experimental design in conjunction with the statistical framework within which to apply the fundamental concepts. The difference between experimental studies and observational studies is addressed, along with a discussion of the various components of experimental design: the error-control design, the treatment design, and the observation design. A series of error-control designs are presented based on fundamental design principles, such as randomization, local control (blocking), the Latin square principle, the split-unit principle, and the notion of factorial treatment structure. This book also emphasizes the practical aspects of designing and analyzing experiments and features:

Increased coverage of the practical aspects of designing and analyzing experiments, complete with the steps needed to plan and construct an experiment
A case study that explores the various types of interaction between both treatment and blocking factors, and numerical and graphical techniques are provided to analyze and interpret these interactions
Discussion of the important distinctions between two types of blocking factors and their role in the process of drawing statistical inferences from an experiment
A new chapter devoted entirely to repeated measures, highlighting its relationship to split-plot and split-block designs
Numerical examples using SAS® to illustrate the analyses of data from various designs and to construct factorial designs that relate the results to the theoretical derivations

Design and Analysis of Experiments, Volume 1, Second Edition is an ideal textbook for first-year graduate courses in experimental design and also serves as a practical, hands-on reference for statisticians and researchers across a wide array of subject areas, including biological sciences, engineering, medicine, pharmacology, psychology, and business.

About the Author

Klaus Hinkelmann, PhD, is Emeritus Professor of Statistics in the Department of Statistics at Virginia Polytechnic Institute and State University. A Fellow of the American Statistical Association and the American Association for the Advancement of Science, Dr. Hinkelmann has published extensively in the areas of design of experiments, statistical methods, and biometry.

The late Oscar Kempthorne, ScD, was Emeritus Professor of Statistics and Emeritus Distinguished Professor of Liberal Arts and Sciences at Iowa State University. He was the recipient of many honors within the statistics profession.

New to Edition

Expanding Chapter 2 to include a more thorough discussion of the planning aspects of setting up an experiment, emphasizing the supporting roles of and interactions between the subject matter scientist and the statistician.
Expanding Chapter 9 to draw important distinctions between two types of blocking factors and to illustrate their roles in the process of drawing statistical inferences from the experiment.
Separating the discussion of repeated measures from the chapter dealing with split-plot designs and making it a separate chapter, explaining how repeated measures can be paired with any error-control design and how this leads formally to a split-plot type structure with correlated observations leading to a mixed model type analysis.
Adding to most chapters numerical examples in the form of giving for a data set the SAS® input statements and commenting on the numerical output, thus linking the results from an experiment to the formal derivations and concepts provided in the earlier part of the chapter.

Features

Increased coverage of the practical aspects of designing and analyzing experiments, complete with the steps needed to plan and construct an experiment
Numerical examples using SAS® to illustrate the analyses of data from various designs and to construct factorial designs that relate the results to the theoretical derivations.
Discussion of the important distinctions between two types of blocking factors and their role in the process of drawing statistical inferences from an experiment.
A case study that explores the various types of interaction between both treatment and blocking factors, and numerical and graphical techniques are provided to analyze and interpret these interactions

Series

Wiley Series in Probability and Statistics

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