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Optimum Experimental Designs, with SAS (Oxford Statistical Science Series) 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024

Optimum Experimental Designs, with SAS (Oxford Statistical Science Series)
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简体网页||繁体网页
A. C. Atkinson 作者
Oxford University Press, USA
译者
2007-07-19 出版日期
528 页数
USD 85.00 价格
Paperback
丛书系列
9780199296606 图书编码

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Optimum Experimental Designs, with SAS (Oxford Statistical Science Series) 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

Optimum Experimental Designs, with SAS (Oxford Statistical Science Series) 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

Optimum Experimental Designs, with SAS (Oxford Statistical Science Series) 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024


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Optimum Experimental Designs, with SAS (Oxford Statistical Science Series) 在线电子书 pdf 下载 txt下载 epub 下载 mobi 在线电子书下载

Optimum Experimental Designs, with SAS (Oxford Statistical Science Series) 在线电子书 图书描述

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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