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Optimum Experimental Designs, With SAS: 34 (Oxford Statistical Science Series) - Hardcover

 
9780199296590: Optimum Experimental Designs, With SAS: 34 (Oxford Statistical Science Series)
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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.
Biografía del autor:
Randall was Chairman, President, and CEO of Eli Lilly and Company until his retirement in 1999, when he was named Chairman Emeritus.

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  • VerlagOUP Oxford
  • Erscheinungsdatum2007
  • ISBN 10 0199296596
  • ISBN 13 9780199296590
  • EinbandTapa dura
  • Anzahl der Seiten528

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9780199296606: Optimum Experimental Designs, with SAS (Oxford Statistical Science Series 34)

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ISBN 10:  019929660X ISBN 13:  9780199296606
Verlag: Oxford University Press, USA, 2007
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Buchbeschreibung Buch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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. Bestandsnummer des Verkäufers 9780199296590

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Anthony (London School of Economics) Atkinson|Alexander (School of Mathematics, University of Manchester) Donev|Randall (SAS Institute Inc.) Tobias
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Buchbeschreibung Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This text focuses on optimum experimental design using SAS, a powerful software package that provides a complete set of statistical tools including analysis of variance, regression, categorical data analysis, and multivariate analysis. SAS codes, results, p. Bestandsnummer des Verkäufers 594424077

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