Optimal Experimental Design with R

Optimal Experimental Design with R book cover

Optimal Experimental Design with R

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

  • Publisher: Chapman and Hall/CRC
  • Publication Date: 18 May 2011
  • Edition: 1st
  • Language: English
  • Print length: 345 pages
  • ISBN-10: 1439816972
  • ISBN-13: 9781439816974

Book Description

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.

    Editorial Reviews

    Review

    the book provides an impressive amount of information that will be greatly helpful to OPDOE users. ... the book provides many examples, mainly from the fields of agriculture and animal science. ... readers will benefit from learning about a number of nifty functions in OPDOE, for example, its sample size solvers.
    --Wayne Adams and Mark Anderson,
    Technometrics, May 2012

    Overall, I think that mathematically apt readers, who want to do sample size determination for nontrivial experimental setups or are interested in the ins and outs of balanced incomplete block designs, will benefit most from the book.
    --Ulrike Grömping,
    Journal of Statistical Software, October 2011

    From the Back Cover

    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.

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