"The book is well laid out and is as beautifully produced as we have come to expect from the Oxford Statistical Science Series, in which this is the eighth volume. . . . a thought-provoking reminder always to consider the objectives when designing experiments." --The Times Higher Education Supplement
"A very interesting book. It should be read by every graduate student and by every statistician who designs or intends to design experiments." --Technometrics
"If you are a believer in D-optimality, or at least wish to act like one, you will find this book excellent....Provides a good basis for a semester's course..." --Journal of the American Statistical Association
Product Description
A well-designed experiment is an efficient method for learning about the physical world, however since experiments in any setting cannot avoid random error, statistical methods are essential for their design and implementation, and for the analysis of results. In this book, the fundamentals of optimum experimental design theory are presented. In the first part, the advantages of a statistical approach to the design of experiments are discussed, and the ideas of models, least squares fitting, and optimum experimental designs are introduced. The second part presents a more detailed discussion of the general theory of optimum design and an evaluation of various criteria that may be appropriate for designing experiments. Specific experiments are detailed and algorithms for the construction of designs are given. Each chapter is a self-contained, illustrated with examples drawn from science and engineering. Little previous statistical knowledge is assumed, and the derivation of mathematical results has been avoided. This book should be of interest to everyone concerned with designing experiments that are practical, efficient, and accurate.
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