Optimum Experimental Designs, With SAS

Anthony Atkinson (London School of Economics), Alexander Donev (Astra Zeneca), Randall Tobias (SAS Institute Inc.)

$357.95

Hardback

Not in-store but you can order this
How long will it take?

Availability Information

We source books from suppliers in Australia and overseas. For books we don't currently have in stock, the time it takes to get them from our suppliers can vary widely - from a few days to a few months - so we check each book with each supplier to determine the expected time it will take to be supplied to us.

We then advise you accordingly. If the time taken to get any book is too long for you, you can let us know and we will cancel or adjust your order, and refund as required.

To find out the anticipated arrival time for specific items prior to ordering, please contact us by phone or email:

Phone +61 2 9264 3111, or 1800 4 BOOKS (1800 4 26657) if outside Sydney:
option 1 Abbey's Bookshop (Crime, History, Science, Kids & more) • info@abbeys.com.au
option 2 Language Book Centre (ESL & Foreign Languages) • language@abbeys.com.au
option 3 Galaxy Bookshop (Sci-fi, Fantasy, Romance, Graphic Novels) • sf@galaxybooks.com.au

QTY:

English

Oxford University Press
07 June 2007

Chemical industries; Pharmaceutical industries; Epidemiology & medical statistics; Probability & statistics; Maths for scientists; Maths for engineers

Series: Oxford Statistical Science Series

"Experiments on patients, processes or plants all have random error, making statistical methods essential for their efficient design and analysis. This book presents the theory and methods of optimum experimental design, making them available through the use of SAS programs. Little previous statistical knowledge is assumed. The first part of the book stresses the importance of models in the analysis of data and introduces least squares fitting and simple optimum experimental designs. The second part presents a more detailed discussion of the general theory and of a wide variety of experiments. The book stresses the use of SAS to provide hands-on solutions for the construction of designs in both standard and non-standard situations. The mathematical theory of the designs is developed in parallel with their construction in SAS, so providing motivation for the development of the subject. Many chapters cover self-contained topics drawn from science, engineering and pharmaceutical investigations, such as response surface designs, blocking of experiments, designs for mixture experiments and for nonlinear and generalized linear models. Understanding is aided by the provision of ""SAS tasks"" after most chapters as well as by more traditional exercises and a fully supported website. The authors are leading experts in key fields and this book is ideal for statisticians and scientists in academia, research and the process and pharmaceutical industries."

By: Anthony Atkinson (London School of Economics), Alexander Donev (Astra Zeneca), Randall Tobias (SAS Institute Inc.)
Imprint: Oxford University Press
Country of Publication: United Kingdom
Volume: 34
Dimensions: Height: 247mm, Width: 173mm, Spine: 33mm
Weight: 1.005kg
ISBN: 9780199296590
ISBN 10: 0199296596
Series: Oxford Statistical Science Series
Pages: 528
Publication Date: 07 June 2007
Audience: Professional and scholarly , Undergraduate
Format: Hardback
Publisher's Status: Active

Preface I Background 1: Introduction 2: Some key ideas 3: Experimental strategies 4: The choice of a model 5: Models and least squares 6: Criteria for a good experiment 7: Standard designs 8: The analysis of experiments II Theory and applications 9: Optimum design theory 10: Criteria of optimality 11: D-optimum designs 12: Algorithms for the construction of exact D-optimum designs 13: Optimum experimental design with SAS 14: Experiments with both qualitative and quantitative factors 15: Blocking response surface designs 16: Mixture experiments 17: Nonlinear models 18: Bayesian optimum designs 19: Design augmentation 20: Model checking and designs for discriminating between models 21: Compound design criteria 22: Generalized linear models 23: Response transformation and structured variances 24: Time-dependent models with correlated observations 25: Further topics 26: Exercises Bibliography Author index Subject index