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eBook Optimum Experimental Designs, with SAS (Oxford Statistical Science Series) epub

by Anthony Atkinson,Alexander Donev,Randall Tobias

eBook Optimum Experimental Designs, with SAS (Oxford Statistical Science Series) epub
  • ISBN: 019929660X
  • Author: Anthony Atkinson,Alexander Donev,Randall Tobias
  • Genre: Science
  • Subcategory: Mathematics
  • Language: English
  • Publisher: Oxford University Press (July 19, 2007)
  • Pages: 528 pages
  • ePUB size: 1486 kb
  • FB2 size 1827 kb
  • Formats doc mobi rtf lit


Experiments on patients, processes or plants all have random error, making statistical methods essential for their efficient design and analysis.

Experiments on patients, processes or plants all have random error, making statistical methods essential for their efficient design and analysis. 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.

Anthony Atkinson, Alexander Donev, and Randall Tobias . Oxford Statistical Science Series. Experienced author team.

Optimum Experimental Designs, with SAS (Oxford Statistical Science .

Optimum Experimental Designs, with SAS (Oxford Statistical Science Series). Design and Analysis of Experiments. The book is well laid out and is as beautifully produced as we have come to expect from the Oxford Statistical Science Series, in which this is the eighth volume. a thought-provoking reminder always to consider the objectives when designing experiments. -The Times Higher Education Supplement. A very interesting book. It should be read by every graduate student and by every statistician who designs or intends to design experiments.

Little previous statistical knowledge is assumed.

Optimum Experimental Designs, With SAS - Oxford Statistical Science Series 34 (Hardback). Anthony Atkinson (author), Alexander Donev (author), Randall Tobias (author). The book stresses the use of SAS to provide hands-on solutions for the construction of designs in both standard and non-standard situations.

Alexander Donev is with Astra Zeneca. a very apt blend of theoretical development and practical examples.

book by Randall Tobias. Experiments on patients, processes or plants all have random error, making statistical methods essential for their efficient design and analysis.

Optimum Experimental Designs, with SAS Atkinson, Anthony; Donev, Alexander; Tobias, Randa Oxford Academ 9780199296606 : This text focuses on optimum experimental design using SAS, a powerful .

Anthony Atkinson, Alexander Donev. The first part of the book stresses the importance Experiments on patients, processes or plants all have random error, making statistical methods essential for their efficient design and analysis.

This book is the third volume in a data mining series, with the two previous ones, authored byDaniel . Conjugate direction/gradient methods a statistical and a recursive view12. Experimental designs. 3. Observational studies 11. Study variants applicable to4.

This book is the third volume in a data mining series, with the two previous ones, authored byDaniel Larose, entitled Discovering Knowledge in Data: An introduction to Data Mining andData Mining Methods and Models.

RePEc working paper series dedicated to the job market. Pretend you are at the helm of an economics department.

Handle: RePEc:bla:istatr:v:75:y:2007:i:3:p:413-413. as. HTML HTML with abstract plain text plain text with abstract BibTeX RIS (EndNote, RefMan, ProCite) ReDIF JSON. Download full text from publisher. RePEc working paper series dedicated to the job market.

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.
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