As recently as a decade ago our students used to ask us, “How do I use statistics?” Today we more often hear, “Why should I use statistics?,” Essential Statistics in Business and Economics has attempted to provide real meaning to the use of statistics in our world by using real business situations and real data and appealing to your need to know why rather than just how.

With over 50 years of teaching statistics between the two of us, we feel we have something to offer you—the 21st-century student. Seeing how you’ve changed as the new century unfolds has required us to adapt and seek out better ways of instruction. So we wrote Essential Statistics in Business and Economics to meet four distinct objectives that we felt were not being met by the many textbooks currently available.

Objective 1: Communicate the Meaning of Variation in a Business Context Variation exists everywhere in the world around us. Successful businesses know how to measure variation. They also know how to tell when variation should be responded to and when it should be left alone. We’ll show you how businesses do this.

Objective 2: Use Real Data and Real Business Applications Examples, case studies, and problems are taken from published research or real applications whenever possible. Hypothetical data are used when it seems the best way to illustrate a concept. You can usually tell the difference by examining the footnotes citing the source.

Objective 3: Incorporate Current Statistical Practices and Offer Practical Advice With the increased reliance on computers, statistics practitioners have changed the way they use statistical tools. We’ll show you the current practices and explain why they are used the way they are. We will also tell you when each technique should not be used.

Objective 4: Provide More In-Depth Explanation of the Why and Let the Software Take Care of the How It is critical that you understand the importance of communicating with data. Today’s computer capabilities make it much easier to summarize and display data than ever before. We demonstrate easily mastered software techniques using the common software that is available. We also spend a great deal of time on the idea that there are risks in decision making and those risks should be quantified and directly considered in every business decision.

Our experience tells us that you want to be given credit for the experience you bring to the college classroom. We have tried to honor this by choosing examples and exercises set in situations that will draw on your already vast knowledge of the world around you and knowledge you have gained from other classes you have taken. Emphasis is on thinking about data, choosing appropriate analytic tools, using computers effectively, and recognizing limitations of statistics. We bring your attention to newer methods of analysis that are changing the field of statistics. Business disciplines have adapted to the world around us and we have responded to this by emphasizing applications in health care administration, economics, and entrepreneurship.

There are different types of software for statistical analysis, ranging from Excel’s functions to stand-alone packages. Excel is used throughout this book because it is available everywhere. But calculations are illustrated using MegaStat, whose Excel-based menus and spreadsheet format offer more capability than Excel’s Data Analysis Tools. MINITAB menus and examples are also included to point out similarities and differences of these tools. To assist those of you who need extra help or “catch up” work, the student CD contains tutorials or demonstrations on using Excel or MINITAB for the tasks of each chapter. At the end of each chapter is a list of LearningStats and Visual Statistics demonstrations, case studies, and applications that illustrate the concepts from the chapter. From the CD, you can install MegaStat, LearningStats, and Visual Statistics on your own computer.

Math Level

The assumed level of mathematics is pre-calculus, though there are rare references to calculus where it might help the better-trained reader. All but the simplest proofs and derivations are omitted, but key assumptions are stated clearly. You are advised what to do when these assumptions are not fulfilled. Worked examples are included for basic calculations, but the textbook does assume that computers will do all calculations after the statistics class is over. Thus, interpretation is paramount. End-of-chapter references and suggested Web sites are given so that interested readers can deepen their understanding. LearningStats includes a brief review and self-test on basic math concepts used in the textbook.

Exercises

Simple practice exercises are placed within each section. End-of-chapter exercises tend to be more integrative or to be embedded in more realistic contexts. The end-of-chapter exercises encourage you to try alternative approaches and discuss ambiguities or underlying issues when the statistical tools do not quite “fit” the situation. Many exercises invite mini-essays (at least a sentence or two) rather than just quoting a formula. Exercises marked * involve optional chapter material or more time-consuming answers (not tougher math). Answers to oddnumbered exercises are in the back of the book. The CD has Excel data sets for each chapter’s examples and exercises, so there is no need to enter a lot of data.

LearningStats is a major supplement. It is intended to let you explore data and concepts at your own pace, ignoring material you already know and focusing on things that interest you. Students who have used say that they continue to find it useful after the class is over, sometimes for projects in other classes they are taking or to finally understand a difficult concept (e.g., what does 95 percent confidence mean?). is a menu-driven system that has two parts:

Demonstrations
Illustrations, examples, and case studies using MicrosoftTM Excel, PowerPoint, and Word, with suggested exercises for individual inquiry. Many case studies use simulation (e.g., to illustrate sampling). Samples of student reports and presentations are included for chapters that require data analysis.

Data Sets
Thousands of variables, many of which were collected by students. Files are grouped by data type (cross-sectional or time-series) and topic (e.g., food, health, etc.). In some data sets, short file names are provided to facilitate import of data into MINITABTM or other statistical packages (e.g., Visual Statistics, SPSS).

ACKNOWLEDGMENTS

The authors would like to acknowledge some of the many people who have helped us with Applied Statistics in Business and Economics, from which this shorter version is derived. Dorothy Duffy permitted use of the chemistry lab for the experiments on Hershey Kisses, Brach’s jelly beans, and Sathers gum drops. Nainan Desai and Robert Edgerton explained the proper use of various kinds of engineering terminology. Case studies and examples were suggested by Kevin S. Nathan and Kenneth M.York. Thomas W. Lauer and Floyd G.Willoughby permitted quotation of a case study. Richard W. Hartl of Memorial Hospital and Kathryn H. Sheehy of Crittenton Hospital provided data for case studies. Kevin Murphy, John Sase, T.J. Wharton, and Kenneth M.York permitted questionnaires to be administered in their classes. Ian S. Bradbury,WinsonTaam, and especially RonTracy and Robert Kushler gave generously of their time as expert statistical consultants. Don Smith and Dana Cobb contributed greatly to the databases. Jonathan G. Koomey of E.O. Lawrence Berkeley National Laboratory offered valuable suggestions on visual data presentation.

Mark Isken has reliably provided Excel expertise and has suggested health care applications for examples and case studies. John Seeley and Jeff Whitbey provided regression databases. John Savio and the Michigan State Employees Credit Union providedATMdata. The Siena Research Institute has made its poll results available. The Public Interest Research Group of Michigan (PIRGIM) has generously shared data from its field survey of prescription drug prices.

We are grateful for the careful proofreading and suggestions offered by Frances J. Williams, William G. Knapp, John W. Karkowski, Nirmala Ranganathan, Thomas H. Miller, Clara M. Michetti, Fielder S. Lyons, Catherine L. Tatem, Anup D. Karnalkar, Richard G. Taylor, Ian R. Palme, Rebecca L. Curtiss, and Todd R. Keller. Dozens of other individuals have provided examples and cases which are cited in the text and LearningStats software.

For reviewing the material on quality, we wish to thank Kay Beauregard, Administrative Director at William Beaumont Hospital, and Ellen Barnes and Karry Roberts of Ford Motor Company. Reviewers of the software have made numerous suggestions for improvement, which we have tried to incorporate. In particular, we wish to thank Lari H. Arjomand of Clayton College & State University, Richard P. Gebhart of the University of Tulsa, Kieran Mathieson of Oakland University, Vincent F. Melfi of Michigan State University, J. Burdeane Orris of Butler University, Joe Sullivan of Mississippi State University, and Donald L. Westerfield of Webster University.

A special debt of gratitude is due to Carol Rose for her careful copyediting and editorial suggestions, Wanda Zeman for coordinating the project, and especially Dick Hercher for guiding us at every step, solving problems, and encouraging us along the way. We are grateful to Ardith Baker of Oral Roberts University for her timely and detailed suggestions for improving the manuscript. Special thanks to Jacquelynne McLellan, Frostburg State University, and Lawrence Moore, Alleghany College of Maryland for accuracy checking the manuscript and page proofs. Thanks to the many reviewers who provided such valuable feedback including criticism which made the book better, some of whom reviewed several drafts of the manuscript. Any remaining errors or omissions are the authors’ responsibility.

Thanks to the participants in our focus groups and symposia on teaching business statistics in Chicago, Burr Ridge, Huntington Beach, Las Vegas, and Pasadena who provided so many teaching ideas and insights into their particular students and courses. We hope you will be able to see in the book and the teaching package consideration of those ideas and insights.