Cover image for Design and analysis of experiments with R
Title:
Design and analysis of experiments with R
Personal Author:
Series:
Chapman & Hall/CRC texts in statistical science series
Publication Information:
Boca Raton : CRC Press, Taylor & Francis Group, 2015
Physical Description:
xxiii, 596 pages : illustrations ; 25 cm.
ISBN:
9781439868133

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30000010345728 QA276.6 L39 2015 Open Access Book Book
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Summary

Summary

Design and Analysis of Experiments with R presents a unified treatment of experimental designs and design concepts commonly used in practice. It connects the objectives of research to the type of experimental design required, describes the process of creating the design and collecting the data, shows how to perform the proper analysis of the data, and illustrates the interpretation of results.

Drawing on his many years of working in the pharmaceutical, agricultural, industrial chemicals, and machinery industries, the author teaches students how to:

Make an appropriate design choice based on the objectives of a research project Create a design and perform an experiment Interpret the results of computer data analysis

The book emphasizes the connection among the experimental units, the way treatments are randomized to experimental units, and the proper error term for data analysis. R code is used to create and analyze all the example experiments. The code examples from the text are available for download on the author's website, enabling students to duplicate all the designs and data analysis.

Intended for a one-semester or two-quarter course on experimental design, this text covers classical ideas in experimental design as well as the latest research topics. It gives students practical guidance on using R to analyze experimental data.


Author Notes

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


Table of 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