Table Of ContentSpringer Texts in Statistics
Advisors:
George Casella Stephen Fienberg Ingram Olkin
Springer Science+Business Media, LLC
Springer Texts in Statistics
Alfred: Elements of Statistics for the Life and Social Sciences
Berger: An Introduction to Prob ability and Stochastic Processes
Bilodeau and Brenner: Theory of Multivariate Statistics
Biom: Probability and Statistics: Theory and Applications
Brockwell and Davis: An Introduction to Times Series and Forecasting
Chow and Teicher: Probability Theory: Independence, Interchangeability,
Martingales, Third Edition
Christensen: Plane Answers to Complex Questions: The Theory of Linear
Models, Second Edition
Christensen: Linear Models for Multivariate, Time Series, and Spatial Data
Christensen: Log-Linear Models and Logistic Regression, Second Edition
Creighton: A First Course in Probability Models and Statistical Inference
Dean and Voss: Design and Analysis ofExperiments
du Toit, Steyn, and Stumpf Graphical Exploratory Data Analysis
Durrett: Essentials of Stochastic Processes
Edwards: Introduction to Graphical Modelling, Second Edition
Finkelstein and Levin: Statistics for Lawyers
Flury: A First Course in Multivariate Statistics
Jobson: Applied Multivariate Data Analysis, Volume I: Regression and
Experimental Design
Jobson: Applied Multivariate Data Analysis, Volume 11: Categorical and
Multivariate Methods
Kalbjleisch: Probability and Statistical Inference, Volume I: Probability,
Second Edition
Kalbjleisch: Probability and Statistical Inference, Volume 11: Statistical
Inference, Second Edition
Karr: Probability
Keyjitz: Applied Mathematical Demography, Second Edition
Kiefer: Introduction to Statistical Inference
Kokoska and Nevison: Statistical Tables and Formulae
Kulkarni: Modeling, Analysis, Design, and Control of Stochastic Systems
Lehmann: Elements ofLarge-Sample Theory
Lehmann: Testing Statistical Hypotheses, Second Edition
Lehmann and Casella: Theory ofPoint Estimation, Second Edition
Lindman: Analysis ofVariance in Experimental Design
Lindsey: Applying Generalized Linear Models
Madansky: Prescriptions for Working Statisticians
McPherson: Applying and Interpreting Statistics: A Comprehensive Guide,
Second Edition
Mueller: Basic Principles of Structural Equation Modeling: An Introduction to
LISREL and EQS
(continued after index)
GIen McPherson
Applying and
Interpreting Statistics
A Comprehensive Guide
Second Edition
With 64 Figures
, Springer
Glen McPherson
School ofMathematicsand Physics
The University ofTasmania
Hobart,Tasmania7001
Australia
[email protected]
EditorialBoard
George Casella Stephen Fienberg Ingram Olkin
DepartmentofStatistics DepartmentofStatistics DepartmentofStatistics
UniversityofFlorida CamegieMellon University Stanford University
P.O.Box 118545 Pittsburgh, PA 15213-3890 Stanford, CA94305
Gainesville,FL32611-8545 USA USA
USA
Coverillustration:Aportion ofFigure 17.7.2,which illustratestheposition ofthefirstcanonicalvariable axis
inamultivariateanalysis.
Library ofCongressCataloging-in-PublicationData
McPherson,Gien.
Applying and interpretingstatistics: acomprehensiveguide/GlenMcPherson.-2nded.
p.cm.- (Springertexts instatistics)
Rev.ed.of: Statistics inscientific investigation.c1990.
Includes bibliographical referencesand index.
I.Research-Statistical methods. 2.Science-Statisticalmethods. 3.Statistics.
I.McPherson, Gien. Statistics inscientific investigation. 11.Title. III.Series.
QI80.55.S7 M36 2001
507'.2-dc21 ()()-056318
Printed onacid-freepaper.
Microsoft, Windows, Excel, and Word are registered trademarks of Microsoft Corporation; MINITAB is a
registeredtrademarkofMinitab, Inc.;SAS isaregisteredtrademarkofTbe SASInstitute,Inc.;andSPSS isa
registeredtrademarkofSPSS, Inc.
First edition, Statistics inScientific Investigation:ItsBasis,Application, andInterpretation, © 1990Springer
Verlag New York, Inc.
ISBN 978-1-4419-2879-5 ISBN978-1-4757-3435-5(eBook)
DOI 10.1007/978-1-4757-3435-5
© 2001SpringerScience+BusinessMediaNewYork
OriginallypublishedbySpringer-VerlagNewYork,Incin2001.
Softcoverreprintofthehardcover2ndedition2001
Allrightsreserved.Tbisworkmaynotbetranslated orcopiedinwholeorinpartwithoutthewrittenpermission
of thepublisherSpringerScience+BusinessMedia,LLC,except for
briefexcerpts inconnectionwithreviewsorscholarly analysis. Useinconnection withanyformofinformation
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known or hereafterdeveloped isforbidden.
Tbe useofgeneral descriptivenames, trade names, trademarks,etc., inthispublication, even iftheformer are
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Productionmanaged by Francine McNeill;manufacturingsupervisedbyJerome Basma.
Photocomposedcopy prepared from the author's LaTeX files.
9 8 7 654 3 2 1
SPIN 10751768
Affectionately dedicated to Wendy, Ewen, and Meegan,
to my mother,
and to the memory of my father.
Preface to the Second Edition
In the period since the first edition was published, I have appreciated the corre
spondence from all parts of the world expressing thanks for the presentation of
statistics from a user's perspective. It has been particularIy pleasing to have been
invited to contribute to course restructuring and development based on the ap
proach to learning and applying statistics that underlies this book. In addition, I
have taken account of suggestions and criticisms, and I hope that this new edition
will address all major concerns.
The range of readily accessible statistical methods has greatly expanded over the
past decade, particularly with the growing accessibility of comprehensive statisti
cal computing packages. The approach adopted in this book has anticipated the
changes by its emphasis on building understanding and skills in method selection
and interpretation of findings. There has been a reduction in computational for
mulas to reflect the fact that basic statistical analyses are now almost universally
undertaken on computers. This has allowed the inclusion of a more general cover
age of unifying methodology, particularly Generalized linear methodology, which
permits users to more accurately match their requirements to statistical models
and methods.
A major addition is a chapter on the commonly used multivariate methods.
The aim of this chapter is to provide a practical introduction to selected methods
that aids in selection, application, and interpretation of results. This chapter was
requested by readers who find many of the specialist books in this area rather
daunting or who do not wish to spend time studying the methods in depth.
The opening chapter has been revised to reflect the ever-broadening role of
statistics in our society. Increasingly, my statistical colleagues and I are asked
to provide our consulting expertise in areas that previously did not make use
viii Preface to the Second Edition
of statistical tools. I highlight the growing role for statistics in a world where
accountability is the key, noting how statistics can playa pivotal role for researchers
seeking grants, and research and development departments seeking funds or trying
to ensure that management understand the importance of their findings and their
contributions.
In this edition, there is a maintenance of the aim of making statistics accessible to
readers who lack calculus or matrix algebra. However, for mathematically advanced
readers, the latter sections of Chapter 5 contain the basic elements of probability
theory that underlie the statistical development of the book.
As in the first edition, real-life examples from a broad range of areas of appli
cation are the lifeblood of this book. They continue to reflect the basic premise
underlying the book, namely, the need for statistics to be seen as an integral com
ponent of investigation that examines questions and provides answers that can be
expressed in plain English rather than in mathematical jargon.
My thanks go to the readers and colleagues who have provided valuable com
ment on the book, and to Springer-Verlag New York, Inc., and their staff for the
exceptionally high quality of publishing support they have provided. But all of this
would be to no avail without the deep and continuing support and understanding
of my wife, Wendy, who had to suffer the (figurative) loss of a husband for peri
ods during book writing and editing. To Wendy, I express a deep debt of gratitude.
Hobart, Tasmania, Australia GIen McPherson
Preface to the First Edition
In this book, I have taken on the challenge of providing an insight into statistics
and a blueprint for statistical application for a wide audience. For students in
the sciences and related professional areas and for researchers who may need to
apply statistics in the course of scientific experimentation, the development em
phasizes the manner in wh ich statistics fits into the framework of the scientific
method. Mathematics students will find a unified, but nonmathematical, structure
for statistics that can provide the motivation for the theoretical development found
in standard texts on theoretical statistics. For statisticians and students of statis
tics, the ideas contained in the book and their manner of development may aid in
the development of better communication between scientists and statisticians.
The demands made of readers are twofold:
• a minimal mathematical prerequisite, which is simply an ability to comprehend
formulas containing mathematical variables, such as those derived from a high
school course in algebra or the equivalent; and
• a grasp of the process of scientific modeling, which comes with either experience
in scientific experimentation or practice with solving mathematical problems.
The base on which this book is developed differs from that found in the myr
iad of standard introductory books on "applied statistics." The common approach
takes what might be termed the statistician's view of statistics. The reader is
presented with the tools of statistics and applications of those tools based on a
methodological taxonomy. There is a danger with this approach that the essen
tial structure and function of statistics will not be grasped, leading to misuse of
statistics. In books divided on methodological grounds, the opportunity for com-
x Preface to the First Edition
paring alternative methodologies is diminished, lessening the guidance in method
selection.
The opening chapters of this book provide a user's view of statistics in the form
of a unified and cohesive framework for statistics on which to hang the theory and
applications that follow. The role of prob ability, examples of statistical models,
and the general theoretical constructs are fitted within the basic structure. In
considering applications of statistics, grouping is based on experimental quest ions
rather than on methodological considerations.
The material in this book is a portion of a comprehensive structure of statistics
that I have constructed during my twenty years of academic life as a teacher and
consultant. The remaining material is to be published in two more books that are
in preparation. The structure has been guided by two basic principles:
• a need for a simple but comprehensive view of statistics; and
• the requirement that any description be understandable by readers in their
own language.
The comprehensive aspect is difficult to satisfy, because there are a number of
schools of statistics. The contents of this book naturally reflect my leanings, but
I believe that ablend of different approaches is optimal and have attempted to
develop a view of statistics that presents the several approaches as variations on
one theme rather than as antagonists to that theme.
Since my aim is to explain statistics in the language of the experimenter, I make
many references to real-life experiments. With few exceptions, these are based on
data from my own consulting work, although in some cases I have used a little
"statistical" license because the experimenter did not wish to have the material
published, because I was critical of the experimental practice or the statistical
analysis employed, or because a modification of quest ion or data suited my needs.
I have been forced to simplify or vary the scientific explanation of many of the
examples in order that the statistical point not be submerged in the description.
I apologize in advance for the scientific incompleteness of the descriptions and
urge that the conclusions and interpretations be considered only in the context of
examples of statistical applications. The use of real-life examples is necessary to
establish the importance of experience in any application of statistics and to em
phasize that real-life applications of statistics involve more than a routine process
of putting numbers into formulas and mechanically drawing conclusions.
The decision of which topics to include and the depth to which chosen topics
should be covered has been one of the most difficult aspects in the preparation of
the book. I am conscious of the fact that others would have chosen differently, and
I would appreciate comments from readers regarding areas that they believe should
be included, expanded, or perhaps excluded. While I have made every endeavor
to make the book error free, I am only too aware that in a book of this size and
breadth there will be typing and possibly statistical errors. While I acknowledge
the assistance of others in the preparation of the book, I take sole responsibility
for these errors.
