Experimental design : unified concepts, practical applications, and computer implementation

274 Pages·2015·7.63 MB·English

by  Bowerman

THE BUSINESS Experimental Design •B Quantitative Approaches
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Two procedures are generally used to analyze experimental Design
world business experience
design data—analysis of variance (ANOVA) and r egression
into course readings and
analysis. Because ANOVA is more intuitive, this book devotes
reference materials for
most of its first three chapters to showing how to use
students expecting to tackle ANOVA to analyze balanced (equal sample size) experimental
Unified Concepts,
management and leadership design data.
challenges during their The text first discusses regression analysis at the end
professional careers. of Chapter 2, where regression is used to analyze data that Practical
cannot be analyzed by ANOVA: unbalanced (unequal sample
POLICIES BUILT size) data from two-way factorials and data from incomplete
BY LIBRARIANS block designs. Regression is then used again in Chapter 4 to
Applications,
analyze data resulting from two-level fractional factorial and
• Unlimited simultaneous
block confounding experiments.
usage
• Unrestricted downloading Bruce L. Bowerman is professor emeritus of decision sciences and Computer
and printing at Miami University in Oxford, Ohio. He received his PhD d egree
• Perpetual access for a in statistics from Iowa State University in 1974 and has over E
forty years of experience teaching basic statistics, regression X Implementation
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comprehensive, cost-effective of experience teaching basic statistics, regression analysis, ES Richard T. O’Connell
way to deliver practical time series forecasting, quality control, and other courses. IG
Professor O’Connell has been the recipient of an Effec tive N Emily S. Murphree
treatments of important
Educator award from the Richard T. Farmer School of Business
business issues to every
Administration at Miami.
student and faculty member.
Emily S. Murphree is professor emeritus of statistics at Miami
University, Oxford, Ohio. She received her PhD in statistics
from the University of North Carolina with a research
concentration in applied probability. Professor Murphree
For further information, a received Miami’s College of Arts and Sciences Distinguished
free trial, or to order, contact:  Education Award and has received various civic awards.
[email protected]
Quantitative Approaches
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to Decision Making Collection
Donald N. Stengel, Editor
ISBN: 978-1-60649-958-0
Experimental Design

Experimental Design
Unified Concepts, Practical
Applications, and Computer
Implementation
Bruce L. Bowerman, Richard T. O’Connell, and
Emily S. Murphree
Experimental Design: Unified Concepts, Practical Applications, and
Computer Implementation
Copyright © Business Expert Press, LLC, 2015.
All rights reserved. No part of this publication may be reproduced,
stored in a retrieval system, or transmitted in any form or by any
means—electronic, mechanical, photocopy, recording, or any other
except for brief quotations, not to exceed 400 words, without the prior
permission of the publisher.
First published in 2015 by
Business Expert Press, LLC
222 East 46th Street, New York, NY 10017
www.businessexpertpress.com
ISBN-13: 978-1-60649-958-0 (paperback)
ISBN-13: 978-1-60649-959-7 (e-book)
Business Expert Press Quantitative Approaches to Decision Making
Collection
Collection ISSN: 2163-9515 (print)
Collection ISSN: 2163-9582 (electronic)
Cover and interior design by Exeter Premedia Services Private Ltd.,
Chennai, India
First edition: 2015
10 9 8 7 6 5 4 3 2 1
Printed in the United States of America.
Abstract
Experimental Design: Unified Concepts, Practical Applications, and Com-
puter Implementation is a concise and innovative book that gives a complete
presentation of the design and analysis of experiments in approximately
one half the space of competing books. With only the modest prerequisite
of a basic (noncalculus) statistics course, this text is appropriate for the
widest possible audience.
Keywords
experimental design, fractional factorials, Latin square designs, nested
designs, one factor analysis, one-way ANOVA, randomized block design,
response surfaces, split plot design, two factor analysis, two level factorial
designs, two-way ANOVA

Contents
Preface ��������������������������������������������������������������������������������������������������ix
Chapter 1 An Introduction to Experimental Design:
One Factor Analysis .......................................................1
Chapter 2 Two Factor Analysis ....................................................45
Chapter 3 More Advanced Experimental Designs ......................125
Chapter 4 Two Level Factorials, Fractional Factorials,
Block Confounding, and Response Surfaces ..............179
Appendix A Statistical Tables .........................................................249
References �������������������������������������������������������������������������������������������257
Index �������������������������������������������������������������������������������������������������259

Preface
Experimental Design: Unified Concepts, Practical Applications, and Com-
puter Implementation is a concise and innovative book that gives a c omplete
presentation of the design and analysis of experiments in approximately
one half the space of competing books. With only the modest prereq-
uisite of a basic (noncalculus) statistics course, this text is appropriate
for the widest possible audience—college juniors, seniors, and first year
graduate students in business, the social sciences, the sciences and statis-
tics, as well as professionals in business and industry. Using a unique and
integrative approach, this text organizes and presents the two procedures
for analyzing experimental design data—analysis of variance (ANOVA)
and regression analysis—in such a way that the reader or instructor can
move through the material more quickly and efficiently than when using
competing books and so that the true advantages of both ANOVA and
regression analysis are made clearer.
Because ANOVA is more intuitive, this book devotes most of its first
three chapters to showing how to use ANOVA to analyze the type of
experimental design data that it can be validly used to analyze: balanced
(equal sample size) data or unbalanced (unequal sample size) data from
one factor studies, balanced data from two factor studies (two-way
factorials and randomized block designs), and balanced data from three
or more factor studies. Chapter 3 includes a general ANOVA procedure
for analyzing balanced data experiments.
Regression analysis can be used to analyze almost any balanced or
unbalanced data experiment but is less intuitive than ANOVA. Therefore,
this book waits to discuss regression analysis until it is needed to analyze
data that cannot be analyzed by ANOVA. This is in Section 2.4, where
the analysis of unbalanced data resulting from two-way factorials is dis-
cussed. Waiting until Section 2.4, gives more space to explain regression
analysis from first principles to readers who have little or no background
in this subject and also allows concise discussion of the regression anal-
yses of one factor studies and incomplete block designs. Section 2.4 also