Continuing a best-selling tradition, the third edition of Quality by Experimental Design uses the same easy-to-read and understand format that made the previous two editions so popular with newcomers and experienced readers alike. Completely revised and revamped, the third edition has lost none of the features that made each of the previous editions bestsellers in their own right. Written in Thomas Barker's trademark, conversational style, the third edition includes new topics on inference, more realistic practice problems, examples using Minitab®, and a large dose of Robust Design philosophy and methods. Barker integrates the Robust Design, sometimes known as the Taguchi approach, as a natural part of the design effort and establishes a criterion for measurement variables. He provides step-by-step guides to the Minitab software that give you the ability to apply the concepts in practical applications and includes easy to use experimental design templates. The author presents the mathematical aspects of statistical experimental design in an intuitive rather than a theoretical manner. Emphasizing both the philosophy and the techniques for setting up experiments, the book shows you how to achieve increased efficiency, timely accomplishment of goals, visualization through graphical and numerical representation, and control of the experiment through careful planning. Those new to QED will find some of the most powerful ideas in scientific investigation and engineering understanding in this book. Seasoned QED'ers will appreciate the new insight it offers and timely reviews of subjects in which they may have become a bit rusty.
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"With a healthy dosage of exclamatory sentences and unique analogies (one even involving Robin Hood and Friar Tuck) in the first pages of the book, the author does not fail to meet expectations."
-Robert G. McLeod, Journal of Quality Technology, Vol. 38, No. 4, October 2006
"What distinguishes this book from other introductory texts in experimental design is its writing style. The book maintains a conversational tone throughout, presenting equations and mathematical derivations only when absolutely necessary. Reading it gives the feeling of attending a seminar or chatting with an expert a specific topic...The author clearly relishes this approach, and it often works well, making the chapters easy and quick to read and understand. It also has the advantage of appealing to math-phobic readers and anyone trying to avoid feeling lectured."
"Quality by Experimental Design has a lively style and enough tantalizing material that, I hope, will make beginners in statistics, and practitioners in other engineering areas, interested in picking up more advanced books to get a deeper look at the application of statistically designed experiments to quality control problems."
-Alejandro Heredia-Langner, Technometrics, Vol. 48, No. 4, November 2006
"...an invaluable text...presents a wide variety of techniques and innovative methods for designing and conducting experiments with an expectation of acquiring actionable knowledge. ...material is presented in a progressive way that thoughtfully discusses and illustrates proven experimental methods that may be employed to make informed decisions."
--Hank Altland, Corning, Inc., Retired
"The book is an introduction to the theory of experimental design for practitioners. ... The different methods and models are illustrated by a large number of examples and exercises taken from practice. For finding the solutions of the problems, the software package Minitab is used. Application of the methods is supported by various templates and worksheets. ..."
-Zentralblatt MATH, 1088
THE PHILOSOPHY OF EXPERIMENTATION
Why Design Experiments?
Organizing the Experiment
The Neglected Response Variable
STATISTICAL EXPERIMENTAL DESIGN
The Factorial 2-Level Design General Factorial Designs
Fractional Factorials at 2-Levels
Multi-Level Designs
3-Level Designs
Randomized Block and Latin Square
Nested Designs
Evolutionary Operation
SORTING THE SIGNAL FROM THE NOISE
Simple Analysis
Analysis of Means by Using the Variance
YATES Analysis Analysis of 2k and 2k-p Designs
Matrix Algebra
Least Squares Analysis
Putting ANOVA and Least Squares to Work
ANOVA for Blocked and Nested Designs
THE DERIVATION OF EMPIRICAL EQUATIONS FROM STATISTICALLY DESIGNED EXPERIMENTS
A Case History of an Experimental Investigation
UTILIZATION OF EMPIRICAL EQUATIONS
Robust Design
Monte Carlo Simulation and Tolerance Design
Case History Completed: The Utilization of the Equation
Statistical Tables
Index
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