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Design and Analysis of Experiments with R

Handbook / Manual
  • Emphasizes the connection between the experimental units, the way treatments are randomized to experimental units, and the proper error term for an analysis of data
  • Uses R throughout to illustrate the construction of experimental designs and analysis of data
  • Provides uniform coverage on experimental designs and design concepts that are most commonly used in practice
  • Presents numerous applications from the pharmaceutical, agricultural, industrial chemicals, and machinery industries
  • Includes exercises at the end of every chapter

Series: Chapman & Hall/CRC Texts in Statistical Science

By: John Lawson (Editor)

596 pages, 100 b/w illustrations, tables

Chapman & Hall (CRC Press)

Hardback | Jan 2015 | #212162 | ISBN-13: 9781439868133
Availability: Usually dispatched within 6 days Details
NHBS Price: £63.99 $80/€74 approx

About this book

One of the first texts to use R to illustrate the construction of experimental designs and analysis of data, Design and Analysis of Experiments with R covers both classical ideas in experimental design and the latest research topics. It clearly discusses the objectives of a research project that lead to an appropriate design choice, the practical aspects of creating a design and performing experiments, and the interpretation of the results of computer data analysis. It also includes many applications from the pharmaceutical, agricultural, industrial chemicals, and machinery industries. A solutions manual is available for qualifying instructors.

"This is an excellent but demanding text. [...] This book should be mandatory reading for anyone teaching a course in the statistical design of experiments. [...] reading this text is likely to influence their course for the better."
MAA Reviews, March 2015


Contents

- Introduction
- Completely Randomized Designs with One Factor
- Factorial Designs
- Randomized Block Designs
- Designs to Study Variances
- Fractional Factorial Designs
- Incomplete and Confounded Block Designs
- Split-Plot Designs
- Crossover and Repeated Measures Designs
- Response Surface Designs
- Mixture Experiments
- Robust Parameter Design Experiments
- Experimental Strategies for Increasing Knowledge
- Bibliography
- Index


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Biography

John Lawson is a professor in the Department of Statistics at Brigham Young University.

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