Experimental design is essential for statistical work in many fields including medicine, agriculture, and engineering. This book will serve as a modern and comprehensive reference. The book includes sample SAS programs.

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This is a readable book presenting the basic concepts, principles, and techniques of design and analysis of experiments. Written with a view to making it accessible to a wide audience, the authors make concerted efforts to avoid using calculus and linear algebra and, wherever needed, a low mathematical level is used for presentation. Rather than performing exploratory data analysis, the concentration here is on the use of prespecified models and preplanned analyses. Model assumptions are clearly stated, and checked through the use of residual plots rather than formal tests. All analyses are presented by using standard linear models under the assumption of normality. It is the experimentwise control of the error rate and confidence levels on which the presentation is focused as opposed to individual error rates and confidence levels. The popular "Taguchi techniques", used extensively in an industrial set-up, are included and appear throughout several chapters.

The book contains enough material for an instructor to offer a course ranging from one semester to one year. An attractive feature of this book is the inclusion of numerous real experiments which were either run by students or extracted from published articles---thus bringing home to students the practical utility of statistical designs. The authors have done a commendable job in presenting, explaining, and elucidating the fundamental concepts of design and analysis of experiments through illustrative examples. A carefully selected set of exercises is provided at the end of each chapter for students to test their understanding of the material.

--Mathematical Reviews

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