"How often have you heard people/students say about a particular subject, 'I'll never use this in the real world?' I thought statistics was a bit on the 'math-geeky' side at first. Imagine my horror when I saw α, R², and correlations on several financial reports at my current job (an intern position at a financial services company). I realized then that I had better try to understand some of this stuff."
- Jill Odette (an introductory statistics student)

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. Seeing how students have 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.

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 students want to be given credit for the experience they bring to the college classroom. We have tried to honor this by choosing examples and exercises set in situations that will draw on students' already vast knowledge of the world and knowledge gained from other classes. Emphasis is on thinking about data, choosing appropriate analytic tools, using computers effectively, and recognizing limitations of statistics.

• Better nontechnical motivation of chapter topics.
• Improved transitions between concepts within chapters.
• More and updated mini cases on topics that will interest students.
• Revisions to graphic illustrations and tables in order to provide a better "picture" of the concept for students.
• More large real data sets for student assignment projects, included on Student CD.
• New exercises and examples using real data from Noodels & Company, a rapidly growing casual dining chain whose success is based on a customer-driven business model and decision making using statistical analysis.
• Updated examples and updated data sets used in exercises.
• Enlarged and improved test bank for instructors.
• Compatibility with Excel 2007 as well as Excel 2003.
• Section exercises for review before exams, with complete solutions (Appendix H).

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, an Excel add-in 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 students who need extra help or "catch up" work, the text website (www.mhhe.com/doaneess2e) contains tutorials or demonstrations on using Excel, MINITAB, or MegaStat 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.

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, though key assumptions are stated clearly. The learner is 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.

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 the learner 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. Answers to odd-numbered exercises are in the back of the book (all answers are in the instructor's manual).

LearningStats is intended to let students explore data and concepts at their own pace, ignoring material they already know and focusing on things that interest them. LearningStats includes explanations on topics that are not covered in other software packages, such as writing effective reports, how to perform calculations, how to make effective charts, or how the bootstrap method works. It also includes some topics that did not appear prominently in the textbook (e.g., stem-and-leaf plots, finite population correction factor, bootstrap simulation techniques). Instructors can use LearningStats PowerPoint presentations in the classroom, but students can also use them for self-instruction. No instructor can "cover everything," but students can be encouraged to explore LearningStats data sets and/or demonstrations perhaps with an instructor's guidance, or even as an assigned project.