Optimum experimental designs
Author(s)
Bibliographic Information
Optimum experimental designs
（Oxford statistical science series, 8）
Clarendon Press , Oxford University Press, 1992
- : hard
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Note
Includes bibliographical references (p. [297]-305) and index
Description and Table of Contents
Description
A well-designed experiment is an efficient method of learning about the world. Because experiments in the field and in the laboratory cannot avoid random error, statistical methods are essential for their efficient design and analysis. In this book, the fundamentals of optimum experimental design theory are presented. In the first part of the part of the book, 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 topic, 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 efficient experiments in the laboratory or in the industry.
Table of Contents
- Part I. Fundamentals
- Introduction
- Some key ideas
- Experimental strategies
- The choice of a model
- Models and least squares
- Criteria for a good experiment
- Standard designs
- The analysis of experiments
- Part II. Theory and applications
- Optimum design theory
- Criteria of optimality
- Experiments with both qualitative and quantitative factors
- Blocking response surface designs
- Restricted region designs
- Failure of the experiment and design augmentation
- Non-linear models
- Optimum Bayesian design
- Discrimination between models
- Composite design criteria
- Further topics.
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