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Optimal Experimental Design with R

By: Albrecht Gebhardt (Author) , Dieter Rasch (Author) , Jurgen Pilz (Author) , L.R. Verdooren (Author)

Manufacture on Demand

Ksh 16,200.00

Format: Paperback or Softback

ISBN-10: 0367382768

ISBN-13: 9780367382766

Publisher: Taylor & Francis Ltd

Imprint: Chapman & Hall/CRC

Country of Manufacture: GB

Country of Publication: GB

Publication Date: Sep 5th, 2019

Publication Status: Active

Product extent: 345 Pages

Weight: 550.00 grams

Dimensions (height x width x thickness): 15.60 x 23.40 x 2.60 cms

Product Classification / Subject(s): Probability & statistics
Technology, engineering, agriculture

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  • Reviews

Optimal Experimental Design with R introduces experimenters to the philosophy of experimentation, and the need for good design and data collection for experiments. It gives experimenters and statisticians guidance on how to construct optimum experimental designs and calculate the sample size needed using R programs. The book contains many detailed real-world examples that show how the R programs should be used. The authors discuss variations of the regression model, including linear and nonlinear regression models. They also provide a final chapter of theoretical details for interested mathematical statisticians.

Experimental design is often overlooked in the literature of applied and mathematical statistics: statistics is taught and understood as merely a collection of methods for analyzing data. Consequently, experimenters seldom think about optimal design, including prerequisites such as the necessary sample size needed for a precise answer for an experimental question.





Providing a concise introduction to experimental design theory, Optimal Experimental Design with R:







  • Introduces the philosophy of experimental design
    Provides an easy process for constructing experimental designs and calculating necessary sample size using R programs
    Teaches by example using a custom made R program package: OPDOE






Consisting of detailed, data-rich examples, this book introduces experimenters to the philosophy of experimentation, experimental design, and data collection. It gives researchers and statisticians guidance in the construction of optimum experimental designs using R programs, including sample size calculations, hypothesis testing, and confidence estimation. A final chapter of in-depth theoretical details is included for interested mathematical statisticians.


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