Statistics for Business and Economics, Global Edition 9th Edition

Book Preface

Business statistics has continued to evolve as a discipline and has become an increasingly important part of business education programs. It is crucial how business statistics  gets taught and what gets taught. Statistics for Business and Economics, ninth edition, has  been written to meet the need for an introductory text that provides a strong introduction to business statistics, develops understanding of concepts, and emphasizes problem  solving using realistic examples that use real data sets and computer based analysis.

These examples highlight business and economics examples for the following:
• MBA or undergraduate business programs that teach business statistics
• Graduate and undergraduate economics programs
• Executive MBA programs
• Graduate courses for business statistics

Designed to build a strong foundation in applied statistical procedures, Statistics for  Business and Economics enables individuals to perform solid statistical analysis in many  business and economic situations. We have emphasized an understanding of the assumptions that are necessary for professional analysis. In particular we have greatly  expanded the number of applications that utilize data from applied policy and research settings. These data and problem scenarios have been obtained from business  analysts, major research organizations, and selected extractions from publicly available data sources. With data analysis software like Microsoft Excel, JMP, and Minitab,  that illustrate how software can assist decision making process, it is now easy to compute, from the data, the output needed for many statistical procedures. It is tempting to merely apply simple “rules” using these outputs—an approach used in many  textbooks. Our approach is to provide instruction through a combination of examples  and exercises, supported by relevant software that show how understanding of methods and their assumptions lead to useful understanding of business and economic  problems.

NEW TO THIS EDITION
The ninth edition of this book has been revised and updated to provide students with improved problem contexts for learning how statistical methods can improve their analysis  and understanding of business and economics.
The objective of this revision is to provide a strong core textbook with new features  and modifications that will provide an improved learning environment for students entering a rapidly changing technical work environment. This edition has been carefully  revised to improve the clarity and completeness of explanations. This revision recognizes  the globalization of statistical study and in particular the global market for this book.
1. Improvement in clarity and relevance of discussions of the core topics included in the  book.
2. Addition of large databases developed by public research agencies, businesses, and  databases from the authors’ own works.
3. An extensive number of new end-of-section or end-of-chapter problems.

CONTINUING FEATURES
1. Addition of a number of case studies, with both large and small sample sizes. Students are provided the opportunity to extend their statistical understanding to the  context of research and analysis conducted by professionals. These studies include  data files obtained from on-going research studies, which reduce for the student, the extensive work load of data collection and refinement, thus providing an emphasis  on question formulation, analysis, and reporting of results.
2. Careful revision of text and symbolic language to ensure consistent terms and definitions and to remove errors that accumulated from previous revisions and production problems.
3. Major revision of the discussion of Time Series both in terms of describing historical  patterns and in the focus on identifying the underlying structure and introductory  forecasting methods.
4. Integration of the text material, data sets, and exercises into new online applications  including MyLab Statistics.
5. Expansion of descriptive statistics to include percentiles, z-scores, and alternative formulae to compute the sample variance and sample standard deviation.
6. Addition of a significant number of new examples based on real world data.
7. Greater emphasis on the assumptions being made when conducting various statistical procedures.
8. Reorganization of sampling concepts.
9. More detailed business-oriented examples and exercises incorporated in the analysis  of statistics.
10. Improved chapter introductions that include business examples discussed in the  chapter.
11. Good range of difficulty in the section ending exercises that permit the professor to  tailor the difficulty level to his or her course.
12. Improved suitability for both introductory and advanced statistics courses for undergraduate and graduate students.
13. Decision Theory, which is covered in other business classes such as operations management or strategic management, has been moved to an online location for access by  those who are interested (www.pearsonglobaleditions.com).

This edition devotes considerable effort to providing an understanding of statistical methods and their applications. We have avoided merely providing rules and canned computer  routines for analyzing and solving statistical problems. This edition contains a complete discussion of methods and assumptions, including computational details expressed in clear and  complete formulas. Through examples and extended chapter applications, we provide guidelines for interpreting results and explain how to determine if additional analysis is required.

The development of the many procedures included under statistical inference and regression  analysis are built on a strong development of probability and random variables, which are a  foundation for the applications presented in this book. The foundation also includes a clear  and complete discussion of descriptive statistics and graphical approaches. These provide important tools for exploring and describing data that represent a process being studied.

Probability and random variables are presented with a number of important applications, which are invaluable in management decision making. These include conditional  probability and Bayesian applications that clarify decisions and show counterintuitive  results in a number of decision situations. Linear combinations of random variables are  developed in detail, with a number of applications of importance, including portfolio  The authors strongly believe that students learn best when they work with challenging and relevant applications that apply the concepts presented by dedicated teachers and  the textbook. Thus the textbook has always included a number of data sets obtained from  various applications in the public and private sectors. In the eighth edition we have added  a number of large data sets obtained from major research projects and other sources.

These data sets are used in chapter examples, exercises, and case studies located at the  end of analysis chapters. A number of exercises consider individual analyses that are typically part of larger research projects. With this structure, students can deal with important  detailed questions and can also work with case studies that require them to identify the  detailed questions that are logically part of a larger research project. These large data sets can also be used by the teacher to develop additional research and case study projects that  are custom designed for local course environments. The opportunity to custom design  new research questions for students is a unique part of this textbook.
A number of major data sets containing Taiwan’s real estate measures, automobile  fuel consumption, health data, the HEI Cost Data Variable Subset (which Includes the  Healthy Eating Index, a measure of diet quality developed by the Economic Research Service and computed for each individual in the survey), New York’s air quality index, and  more are described in detail at the end of the chapters where they are used in exercises  and case studies. A complete list of the data files and where they are used is located at the  end of this preface. Data files are also shown by chapter at the end of each chapter.

The book provides a complete and in-depth presentation of major applied topics. An initial read of the discussion and application examples enables a student to begin working on simple exercises, followed by challenging exercises that provide the opportunity  to learn by doing relevant analysis applications. Chapters also include summary sections, which clearly present the key components of application tools. Many analysts and  teachers have used this book as a reference for reviewing specific applications. Once you  have used this book to help learn statistical applications, you will also find it to be a useful  resource as you use statistical analysis procedures in your future career.
A number of special applications of major procedures are included in various sections. Clearly there are more than can be used in a single course. But careful selection of  topics from the various chapters enables the teacher to design a course that provides for  the specific needs of students in the local academic program. Special examples that can  be left out or included provide a breadth of opportunities. The initial probability chapter,  Chapter 3, provides topics such as decision trees, overinvolvement ratios, and expanded  coverage of Bayesian applications, any of which might provide important material for  local courses. Confidence interval and hypothesis tests include procedures for variances  and for categorical and ordinal data. Random-variable chapters include linear combination of correlated random variables with applications to financial portfolios. Regression applications include estimation of beta ratios in finance, dummy variables in experimental design, nonlinear regression, and many more.

As indicated here, the book has the capability of being used in a variety of courses  that provide applications for a variety of academic programs. The other benefit to the student is that this textbook can be an ideal resource for the student’s future professional  career. The design of the book makes it possible for a student to come back to topics after  several years and quickly renew his or her understanding. With all the additional special  topics, that may not have been included in a first course, the book is a reference for learning important new applications. And the presentation of those new applications follows  a presentation style and uses understandings that are familiar. This reduces the time required to master new application topics.

APPLYING CONCEPTS

We understand how important it is for students to know statistical concepts and apply  those to different situations they face everyday or will face as managers of the future. Almost all sections include examples that illustrate the application of the concepts or methods of that section to a real-world context (even though the company or organization may  be hypothetical). Problems are structured to present the perspective of a decision maker and the analysis provided is to help understand the use of statistics in a practical way.

PROMOTING PROBLEM ANALYSIS
This book includes section Exercises and chapter Exercises and Applications. The section exercises for each chapter begin with straightforward exercises targeted at the topics in each section. These are designed to check understanding of specific topics. Because  they appear after each section, it is easy to turn back to the chapter to clarify a concept or
review a method. The Chapter Exercises and Applications are designed to lead to conclusions about the real world and are more application based. They usually combine concepts and methods from different sections.

ACKNOWLEDGMENTS
We appreciate the following colleagues who provided feedback about the book to guide our  thoughts on this revision: Valerie R. Bencivenga, University of Texas at Austin; Burak Dolar,  Augustana College; Zhimin Huang, Adelphi University; Stephen Lich-Tyler, University of  North Carolina; Tung Liu, Ball State University; Leonard Presby, William Paterson University; Subarna K. Samanta, The College of New Jersey; Shane Sanders, Nicholls State University; Harold Schneider, Rider University; Sean Simpson, Westchester Community College.
The authors thank Dr. Andrea Carlson, Economic Research Service (ERS), U. S. Department of Agriculture, for her assistance in providing several major data files and for guidance in developing appropriate research questions for exercises and case studies. We also  thank Paula Dutko and Empharim Leibtag for providing an example of complex statistical analysis in the public sector. We also recognize the excellent work by Annie Puciloski  in finding our errors and improving the professional quality of this book.  We extend appreciation to two Stetson alumni, Richard Butcher (RELEVANT Magazine) and Lisbeth Mendez (mortgage company), for providing real data from their companies that we used for new examples, exercises, and case studies.
In addition, we express special thanks for continuing support from our families. Bill  Carlson especially acknowledges his best friend and wife, Charlotte, their adult children,  Andrea and Doug, and grandchildren, Ezra, Savannah, Helena, Anna, Eva Rose, and Emily.  Betty Thorne extends special thanks to her best friend and husband, Jim, and to their  family Jennie, Ann, Renee, Jon, Chris, Jon, Hannah, Leah, Christina, Jim, Wendy, Marius,  Mihaela, Cezara, Anda, and Mara Iulia. In addition, Betty acknowledges (in memory)  the support of her parents, Westley and Jennie Moore.
The authors acknowledge the strong foundation and tradition created by the original author, Paul Newbold. Paul understood the importance of rigorous statistical analysis  and its foundations. He realized that there are some complex ideas that need to be developed, and he worked to provide clear explanations of difficult ideas. In addition, he  realized that these ideas become useful only when used in realistic problem solving situations. Thus, many examples and many applied student exercises were included in the  early editions. We have worked to continue and expand this tradition in preparing a book  that meets the needs of future business leaders in the information age.