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Statistical Principles for the Design of Experiments
Applications to Real Experiments

$80.00 USD

Part of Cambridge Series in Statistical and Probabilistic Mathematics

  • Date Published: September 2012
  • availability: This ISBN is for an eBook version which is distributed on our behalf by a third party.
  • format: Adobe eBook Reader
  • isbn: 9781139574884

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About the Authors
  • This book is about the statistical principles behind the design of effective experiments and focuses on the practical needs of applied statisticians and experimenters engaged in design, implementation and analysis. Emphasising the logical principles of statistical design, rather than mathematical calculation, the authors demonstrate how all available information can be used to extract the clearest answers to many questions. The principles are illustrated with a wide range of examples drawn from real experiments in medicine, industry, agriculture and many experimental disciplines. Numerous exercises are given to help the reader practise techniques and to appreciate the difference that good design can make to an experimental research project. Based on Roger Mead's excellent Design of Experiments, this new edition is thoroughly revised and updated to include modern methods relevant to applications in industry, engineering and modern biology. It also contains seven new chapters on contemporary topics, including restricted randomisation and fractional replication.

    • Enables readers to develop designs for their experiments rather than force their experiments into an 'off-the-shelf' design
    • Uses real design problems to illustrate the methodology
    • Authors have extensive experience of consulting on statistical aspects of the design of experiments
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    Product details

    • Date Published: September 2012
    • format: Adobe eBook Reader
    • isbn: 9781139574884
    • contains: 200 b/w illus. 400 tables 80 exercises
    • availability: This ISBN is for an eBook version which is distributed on our behalf by a third party.
  • Table of Contents

    1. Introduction
    2. Elementary ideas of blocking: the randomised complete block design
    3. Elementary ideas of treatment structure
    4. General principles of linear models for the analysis of experimental data
    5. Experimental units
    6. Replication
    7. Blocking and control
    8. Multiple blocking systems and crossover designs
    9. Multiple levels of information
    10. Randomisation
    11. Restricted randomisation
    12. Experimental objectives, treatments and treatment structures
    13. Factorial structure and particular forms of effects
    14. Fractional replication
    15. Incomplete block size for factorial experiments
    16. Quantitative factors and response functions
    17. Multifactorial designs for quantitative factors
    18. Split unit designs
    19. Multiple experiments and new variation
    20. Sequential aspects of experiments and experimental programmes
    21. Designing useful experiments.

  • Instructors have used or reviewed this title for the following courses

    • Design and Analysis of Experiments I
    • Laboratory Operating Standards and Quality Assurance I
    • Statistical Methods: Experimental Design
  • Authors

    R. Mead, University of Reading
    R. Mead is Emeritus Professor of Applied Statistics at the University of Reading.

    S. G. Gilmour, University of Southampton
    S. G. Gilmour is Professor of Statistics in the Southampton Statistical Sciences Research Institute at the University of Southampton.

    A. Mead, University of Warwick
    A. Mead is Senior Teaching Fellow in the School of Life Sciences at the University of Warwick.

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