Design of Comparative Experiments

Erscheinungsjahr 2010
ISBN: 978-0-521-86506-7
Verlag: Cambridge University Press

Buch, Englisch, Band 25, 346 Seiten, Format (B × H): 183 mm x 260 mm, Gewicht: 846 g

Reihe: Cambridge Series in Statistical and Probabilistic Mathematics

This book should be on the shelf of every practising statistician who designs experiments. Good design considers units and treatments first, and then allocates treatments to units. It does not choose from a menu of named designs. This approach requires a notation for units that does not depend on the treatments applied. Most structure on the set of observational units, or on the set of treatments, can be defined by factors. This book develops a coherent framework for thinking about factors and their relationships, including the use of Hasse diagrams. These are used to elucidate structure, calculate degrees of freedom and allocate treatment subspaces to appropriate strata. Based on a one-term course the author has taught since 1989, the book is ideal for advanced undergraduate and beginning graduate courses. Examples, exercises and discussion questions are drawn from a wide range of real applications: from drug development, to agriculture, to manufacturing.

Autoren/Hrsg.

Bailey, R. A.

Fachgebiete

• Mathematik | Informatik Mathematik Stochastik Wahrscheinlichkeitsrechnung
• Interdisziplinäres Wissenschaften Wissenschaften Interdisziplinär Naturwissenschaften, Technik, Medizin
• Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Forschungsmethodik, Wissenschaftliche Ausstattung
• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Datenanalyse, Datenverarbeitung

Inhaltsverzeichnis

Preface
1. Forward look
2. Unstructured experiments
3. Simple treatment structure
4. Blocking
5. Factorial treatment structure
6. Row-column designs
7. Experiments on people and animals
8. Small units inside large units
9. More about Latin squares
10. The calculus of factors
11. Incomplete-block designs
12. Factorial designs in incomplete blocks
13. Fractional factorial designs
14. Backward look
Exercises
Sources of examples, Questions and exercises
Further reading
Bibliography
Index.

Über Autor(innen)

Bailey, R. A.
R. A. Bailey has been Professor of Statistics at Queen Mary, University of London since 1994. She is a fellow of the Institute of Mathematical Statistics and a past president of the International Biometric Society, British Region. This book reflects her extensive experience teaching design of experiments and advising on its application. Her book Association Schemes was published by Cambridge University Press in 2004.