Experiments: Planning, Analysis, and Optimization / Edition 3

by C. F. Jeff Wu, Michael S. Hamada

Overview

Experimental design is one of the most important subjects in statistics. Used in experimental investigations, statistically designed experiments are also a key tool for improving quality in industry and manufacturing. This practical book modernizes experimentation to develop a new system of design and analysis to define the area for years to come. The title's inclusion of modern, never-seen-before topics is compelling and the book will make an excellent complement to Wiley's best-selling Statistics for Experimenters.
MICHAEL HAMADA, PhD, is a technical staff member in the Statistical Sciences Group at Los Alamos National Laboratory in New Mexico. He has published 30 papers and has won the Technometrics' Wilcoxon Prize and the ASQC Brumbaugh Award.

Product Details

ISBN-13:	9781119470106
Publisher:	Wiley
Publication date:	03/30/2021
Series:	Wiley Series in Probability and Statistics , #247
Edition description:	3rd ed.
Pages:	736
Product dimensions:	6.30(w) x 9.10(h) x 1.30(d)

About the Author

C. F. Jeff Wu, PhD, is Coca-Cola Professor in Engineering Statistics at the Georgia Institute of Technology. Dr. Wu has published more than 130 papers and is the recipient of numerous accolades, including the National Academy of Engineering membership and the COPSS Presidents' Award.

Michael S. Hamada, PhD, is Statistical Scientist at Los Alamos National Laboratory in New Mexico. Dr. Hamada is a Fellow of the American Statistical Association and the author of more than seventy published papers.

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Table of Contents

Basic Principles and Experiments with a Single Factor.
Experiments With More Than One Factor.
Full Factorial Experiments at Two Levels.
Fractional Factorial Experiments at Two Levels.
Full Factorial and Fractional Factorial Experiments at Three Levels.
Other Design and Analysis Techniques for Experiments at More Than Two Levels.
Nonregular Designs: Construction and Properties.
Experiments with Complex Aliasing.
Response Surface Methodology.
Introduction to Robust Parameter Design.
Robust Parameter Design for Signal-Response Systems.
Experiments for Improving Reliability.
Experiments With Nonnormal Data.
Appendices.
Indexes.

Editorial Reviews

It is an impressive volume that seems likely to become a standard text.

Short Book Reviews

I agree with the authors that this book is an excellent reference resource for experienced design-of-experiments practitioners.

Technometrics

Wu (statistics and industrial and operations engineering, U. of Michigan-Ann Arbor) and Hamada (statistical science, Los Alamos National Laboratory) introduce some recent discoveries in designing and analyzing experiments to improve industrial products and processes, and their application to system optimization, robustness, and treatment comparison in a number of fields. They describe robust parameter design, improving reliability, analyzing non-normal data, experiments with complex aliasing, multilevel designs, minimum aberrations designs, orthogonal arrays, and other methods. Annotation c. Book News, Inc., Portland, OR (booknews.com)

Booknews

On the whole, I think the book is ideal for a year-long course at the graduate level (there is much more material in the book than can be reasonably covered even in a year-long course), but is still advanced for  undergraduates.”  (Zentralblatt MATH, 2012)

From the Publisher