Statistical reasoning is an essential component of our everyday lives.  We think in terms of probability and constantly make 
inferences about future events.  Whether we acknowledge the role of this type of reasoning on a conscious level is not 
important.  The fact remains that we, as humans, constantly predict the future and constantly use statistical reasoning to 
accomplish this. Given the crucial nature of this type of reasoning, it follows that these skills would be an cardinal 
component of any person's education. 

Thus, the underlying philosophy of this text, Fundamentals of Behavioral Statistics, is that statistical reasoning is a 
crucial element in education.  In this same spirit, this ninth edition extends the book's long tradition of presenting statistical 
reasoning skills in a clear and meaningful way so that readers may understand and learn to appreciate the ubiquitous nature 
of quantitative thinking. 

Today, as we usher in a new millennium, the perceived value of statistical analysis in our lives is more acute than when the 
first edition of this text was written. News papers, national news magazines, and trade journals chronicle the impact of 
statistics. The federal judicial system now requires judges to be conversant in basic statistical principles; these skills are 
needed to determine the merit of testimony offered by expert witnesses. Lawmakers use the results of statistical analysis 
to create policy initiatives that may have a lasting impact on the lives of their constituents. Market researchers test the 
reactions of the public to political events and retail products using focus groups, surveys, and statistical analysis. 
In brief, statistics are everywhere.  

As the role of statistics has become increasingly important in our lives so too has the nature of these analyses evolved.  
Typical undergraduate courses now cover many more types of statistical tests than they did a generation ago.  
The nature of the material itself has become more sophisticated and more powerful.  A greater emphasis is now placed 
on exploration of the data prior to conducting statistical tests.  We now have computers that easily explore the data 
and perform analyses that would otherwise take hours to accomplish manually. Greater thought is now given to the 
importance of issues such as effect size and power analysis prior to conducting an experiment.  Undergraduates now read 
journal articles that discuss the power of the experiment and use tests that were unknown thirty years ago when the first 
edition of this text was published.  So much has changed, yet much remains the same.  The change is clear. 
Statistical analyses have become increasingly sophisticated.  What has remained constant is that we still optimistically 
expect our students to develop their critical thinking skills and use these skills in their coursework and later in their professional lives.

Simplicity & Clarity

Our comprehensive review of statistical procedures strives for simplicity. While we use crucial examples from psychology to guide
the reader, this text is not cluttered with distractions or superfluous information. We have maintained the book's signature of
simplicity even as we have updated the pages with the most significant, recent trends and advances in statistical reasoning.  

Balanced Reasoning  

We believe that that our book strikes a balance between teaching the conceptual foundation of statistics while providing the 
computational foundations of statistics. When Richard Runyon and Audrey Haber wrote the first edition of this book more than 
thirty years ago, they carefully balanced two extremes in teaching statistics: at one extreme, the "cookbook" approach presents 
formulae and leads students through them step-by-step; at the other extreme, statistics is treated as a branch of applied 
mathematics. It is our belief that neither extreme is useful for undergraduates in the behavioral sciences, so 
we continue the critical compromise created in the first edition by carefully integrating the two approaches within this latest revision. 


Critical Thinking Skills   

So much has been written about the value of critical thinking skills, how to foster their development, and how to insure that 
students apply the principles in their lives.  From research on this topic it is clear, critical thinking does not develop in a vacuum. 
Memorized formulas and definitions are of little value.  Blind application of formulas and hours of mind numbing calculations do
nothing to develop critical thinking.   Instead students must expose themselves repeatedly to situations in which they practice 
the application of critical thinking skills. We have endeavored to structure the presentation of the material in a manner that 
allows the student to develop their skills based on quantitative data and well rehearsed application of heuristics.  For 
each test and descriptive statistic we provide the rules and procedures, illustrate their application to relevant examples, 
and then discuss the generalizations that can legitimately drawn from the analysis.    



Useful Pedagogy  

Students who read our textbook will learn about the theory and rationale of the various statistical tests used by behavioral scientists. 
When a statistical concept is introduced in the text, we may illustrate it in a number of ways. We provide both conceptual formulas 
and computational formulas.  At the same time, we use words to explain the rationale of the statistic. Finally, we use visual 
illustration to help convert abstract concepts into images to help the reader understand important principles.  
We recognize that once you have learned the material you will obviously need to review the material either for an exam or for an 
assignment in another course. Whether you use the book as reference or for review we provide the following:


 Basic Math Review:  Appendix A  gives you a quick refresher on basic math

 Statistical Symbols Glossary: Appendix B  references all the major symbols
      you need in clear and straight-forward manner

 Handbook to Fundamental Statistics: The Statistical Formual Guide: Appendix B
	provides a built-in, step-by-step synopsis of formula with useful examples worked out

 Statistical Tables: Appendix D  provides important tables for study

 Summary of Equations: these are found on the front and back inside covers
      of the book and can be used for a quick reference for studying

 Running Glossary: important terms are defined as they are discussed in the text

We understand you probably did not sign up voluntarily to study statistics.  Many of you are taking this course because it is 
required as part of your major or minor concentration.  Others of you are taking it because your parents and counselors have 
suggested a course in statistics to give you a competitive edge in a difficult job market. Many of you expect to go to graduate 
school and are aware of the central importance of analysis of empirical data in that milieu.  Just as the reasons for taking this 
course will vary, so too your backgrounds and prior mathematical experience will vary. 

We know this because we have taught statistics to hundreds of students over many, many years.  And we have learned some 
valuable and surprising things from our students during that time.  For example, we have learned that some students grasp the 
most complex statistical concepts immediately while others have to struggle to master each and every one.  And we have been 
struck by the variety of techniques students find useful and important to them in mastering the material. Their reports vary 
tremendously.  One person will swear by a technique and five others will find it useless.

Our conclusion has been that no one pedagogical technique is successful for all students. Some students have the ability to read 
an equation and immediately understand its workings.  Others have better success when they see an illustration of the concept.  
Some students need verbal descriptions and others find the worked out problems, margin definitions, and end of chapter exercises 
to be the most useful.   It is remarkable, the very same formula or illustration that provides instant insight for one individual can be 
of little or no value to others.

What have these observations meant, in practical terms, for us as authors? We have concluded that it is not enough to provide 
one explanation, one study technique.  We have worked hard to provide you with a range of instructional devices that students 
have told us over the years have worked for them.  We have included techniques useful for learning  the material, for reviewing it at 
exam time and for mastering the calculations required by the exercises.  For example, we have included margin definitions to 
highlight important concepts as they are presented and listings of important terms at the end of each chapter. 
These may be used to guide your learning and to highlight important concepts when you review for exams.  The end of chapter 
exercises provide practice in how to perform the calculations as well as some questions that will force you to think 
about how a statistical test works, why it works that way, and the some of the precautions to take when using the test. 

By the way, the answers to the odd numbered exercises are presented in the appendix. These answers won't tell you exactly how 
to do the calculations but they will serve as a warning if the answer you come up with differs from the one in the text. 

The understanding you develop from your reading and the exercises are reinforced in summary tables in the body of the text.  
We have introduced these summary tables as a way for you to make your study time more efficient.  In one table you can view 
and outline of the major concepts, their characteristics, when they are used, and cautions in their use. We have provided frequently 
used formula and notation in the end pages.    We have included as well a statistical formula guide to give you clear and easy 
access to review of commonly used statistical procedures. This section will be of particular value to you when you study for exams 
and when you finish this course and are called upon in subsequent courses to review a particular statistical technique.

We don't need to tell you that quantitative analysis is an integral part of psychology. Aside from the introductory psychology course, 
behavioral statistics is one of the few common courses for all psychology majors.  You undoubtedly studied statistics as an 
undergraduate and certainly were required to take some statistics courses in graduate school.  In fact you may have used the 
Runyon and Haber text in some of your courses.   If you did then you already know of the long tradition of this text.  We have 
attempted to maintain that tradition and at the same time we have attempted to present new material, reflective of important 
evolution of thought within the field and have deleted material that has outgrown its usefulness.

Two monumental developments within the world of statistics have been the evolving. The first of these has been the increased 
recognition of the importance of power in the design and conduct of experiments.  The second important development has been 
the questioning of the value of statistical hypothesis testing.  In terms of the latter, we recognize that hypothesis testing has its 
limitations, yet we believe that it still can serve a useful function.  Rather than discard hypothesis testing, we show students 
how to analyze the data from a number of perspectives in addition to using traditional hypothesis testing.  In terms of power we 
present the concepts of power and effect size and factors such as sample size and alpha that affect the power of a test.  
Indeed, each chapter related to inferential statistics has a section that reviews issues related to the power of the statistic.

Another addition to the text is the inclusion of clear examples of how to present the results of research in a research paper.  
Several of the chapters now include short examples illustrating the editorial style of the American Psychological Association. 
Learning to write clearly about empirical matters is an important skill that will serve your students well. With respect to maintaining 
the currency of the text, we have removed some material from previous editions and added new material.  We decided to finally 
retire the material on grouped frequency distributions.  Grouped data was once a necessary computational approach.  
The advent of computers and other technological advances has eliminated the need for its inclusion. Instead, we focus more on 
how students can use exploratory data analysis and graphing techniques to augment their analysis of data.

Tradition, our own biases in the teaching of statistics, and reviewers' comments have all influenced the sequence of chapters in 
the text. We recognize that some may not agree with our arrangement.  Thus, we intentionally wrote the chapters to be relatively 
free standing.  In some cases, this is an impossible task.  Testing hypotheses in the chapter on analysis of variance cannot be 
understood without a solid foundation hypothesis testing in general.  We tried to write a text that lends itself to differing orders of 
presentation. 

We hope that you find this as well as other aspects of the text accommodating. 

We would be remiss if we did not publicly acclaim the valued contributions of the many, many individuals who collaborated in the 
development and production of this text.  At each step, from the initial proposal stages to the final production details we were 
blessed with input from individuals who generously provided their time and their talents.  

We must especially mention our Expert Reviewers, Dennis Cogan of Texas Tech
University and Michael Masson of the University of Victoria, Canada.
We would also like to extend our thanks to the following reviewers: 
  
Ken Hobby, Harding University 
Chuck Brainard, University of Arizona 
Fran Conner, University of Alabama
Lisa Isenberg, University of Wisconsin
Stuart Bernstein, Wayne State University
Thomas Billimeck, San Antonio College 
Hilda Williams, Drake Williams College
James Green, University of Connecticut, 
Danuta Bukatko, College of Holy Cross
Philip Tolin, Central Washington University
Rick Jenison, University of Wisconsin - Madison
Elizabeth Kudadjie-Gyamfi, Long Island University -Brooklyn
Stephen Chew, Samford University
Pamela Hunt, College of William and Mary
Siamak Movahedi, University of Massachusetts - Boston
Elizabeth Krupinski, University of Arizona.

We gratefully acknowledge our exceptionally hard working and talented collaborators at McGraw-Hill.  Executive Editor Joe Terry 
skillfully nurtured and coordinated the planning of this revision, along with Susan Kunchandy the Developmental Editor and 
Lai Moy, the Editorial Coordinator. Finally, Fred Speers, our Editorial Assistant must be acknowledged for providing just 
the right proportion of demanding deadlines mixed with words of encouragement that kept our project on schedule.  

We admire and appreciate the efforts of all those named above.

Where do you go from here?   We have outlined for you the multifaceted approach we have taken to provide the techniques and the 
tools to master this material.  What does this approach mean, in practical terms, for you? It means that this text is designed to 
allow you to decide how you should master this material.  We have described the various instructional devices and learning aids.  
Try using these aids.  Find the ones you feel are helpful.  Use them, and keep in mind: the successful students invariably 
try many approaches and study strategies before deciding on the most useful ones. These students actively interact with the study 
materials and use them as tools to develop their own understanding.  Trying to memorize someone else's understanding is of 
little value.   You must be the active learner and critically examine this book and its contents. We give you all you need to become 
a dynamic student in this course.  With some exploration and a bit of effort you have all that you need to acquire a solid, 
successful education in the fundamentals of behavioral statistics.  

There is an entire range of ancillary items which support and enhance this ninth edition:

Student Study Guide
ISBN 	007-232406-6

Instructor's Manual with Test Bank
ISBN 	007-232404-X

Computerized Test Banks for both Windows and Macintosh 
ISBN 	007-232402-3 (MAC)
ISBN 	007-232403-1 (WIN)

Elementary Data Analysis Using Microsoft Excel
by Anita M. Meehan & C. Bruce Warner

ISBN 	0-07-236051-8  
Description: A 128 page Student Guide to Using Microsoft Excel for Data Analysis
Can be bundled and sold as a package with Fundamentals of Behavioral Statistics, 9e Student Textbook

SPSS Online Guide by Richard M. Wielkiewicz (New!) 


Statistics Primer including information on various types of statistics, a statistics glossary, and a practice quiz


Online Resources for Students and Instructors


Instructors Manual (Password Protected ! Instructors Only) 



Feel free to call McGraw-Hill with any questions at 1-800-338-3987, or you can
write to the editorial department with your questions via email. 

Continue Reading About this New 9th Edition For (c) 2000 
 
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