# Statistics for Business & Economics, Revised, 12th Edition

• David R. Anderson
• Dennis J. Sweeney
• Thomas A. Williams
• Jeffrey D. Camm
• James J. Cochran
• ISBN-10: 128584632X
• ISBN-13: 9781285846323
• 1120 Pages | Hardcover
• Previous Editions: 2014, 2011, 2009
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# Overview

The authors bring more than twenty-five years of unmatched experience to this text, along with sound statistical methodology, a proven problem-scenario approach, and meaningful applications that clearly demonstrate how statistical information informs decisions in the business world. Thoroughly updated, the text's more than 350 real business examples, cases, and memorable exercises present the latest statistical data and business information with unwavering accuracy. And, to give you the most relevant text you can get for your course, you select the topics you want, including coverage of popular commercial statistical software programs like Minitab 16 and Excel 2013, along with StatTools and other leading Excel 2013 statistical add-ins. These optional chapter appendices, coordinating online data sets, and support materials like the CengageNOW online course management system, make STATISTICS FOR BUSINESS AND ECONOMICS Revised 12ethe most customizable, efficient, and powerful approach to teaching business statistics available today.

## Features

• All screenshots and instructions in chapter appendices have been updated to Excel 2013, the most recent release of Excel from Microsoft.

• Discrete Probability Distributions--Chapter 5. The introductory material in this chapter has been revised to better explain the role of probability distributions and to show how the material on assigning probabilities in Chapter 4 can be used to develop discrete probability distributions. We point out that the empirical discrete probability distribution is developed by using the relative frequency method to assign probabilities. At the request of many users, we have added a new Section 5.4 that covers bivariate discrete distributions and financial applications. We show how financial portfolios can be constructed and analyzed using these distributions.

• Chapter 12--Comparing Multiple Proportions, Tests of Independence, and Goodness of Fit. This chapter has undergone a major revision. We have added a new section on testing the equality of three or more population proportions. This section includes a procedure for making multiple comparison tests between all pairs of population proportions. The section on the test of independence has been rewritten to clarify that the test concerns the independence of two categorical variables. Revised appendixes with step-by-step instructions for Minitab, Excel, and StatTools are included.

• New Case Problems. We have added 8 new case problems to this edition; the total number of cases is 31. Three new descriptive statistics cases have been added to chapters 2 and 3. Five new case problems involving regression appear in Chapters 14, 15, and 16. These case problems provide students with the opportunity to analyze larger data sets and prepare managerial reports based on the results of their analysis.

• New Statistics in Practice Applications. Each chapter begins with a Statistics in Practice vignette that describes an application of the statistical methodology to be covered in the chapter. New to this edition is a Statistics in Practice for Chapter 2 describing the use of data dashboards and data visualization at the Cincinnati Zoo and Botanical Garden. We have also added a Statistics i Practice to Chapter 4 describing how a NASA team used probability to assist in the rescue of 33 Chilean miners trapped by a cave-in.

• New Examples and Exercises based on Real Data. We continue to make a significant effort to update our text examples and exercises with the most current real data and referenced sources of statistical information. In this edition, we have added approximately 180 new examples and exercises based on real data and referenced sources. Using data from sources also used by The Wall Street Journal, USA Today, Barron's, and others, we have drawn from actual studies to develop explanations and to create exercises that demonstrate the many uses of statistics in business and economics. We believe that the use of real data helps generate more student interest in the material and enables the student to learn about both the statistical methodology and its application. The twelfth edition contains over 350 examples and exercises based on real data.

• InfoTrac® Student Collections are specialized databases expertly drawn from the Gale Academic One library. Each InfoTrac® Student Collection enhances the student learning experience in the specific course area related to the product. These specialized databases allow access to hundreds of scholarly and popular publications - all reliable sources - including journals, encyclopedias, and academic reports. Learn more and access at: http://gocengage.com/infotrac.

• TRUSTED TEAM OF EXPERT AUTHORS ENSURES THE MOST ACCURATE, PROVEN PRESENTATION. As prominent, respected leaders and active consultants in business and statistics today, authors David R. Anderson, Dennis J. Sweeney, and Thomas A. Williams, now joined by Jeffrey D. Camm and James J. Cochran provide an accurate presentation of statistical concepts you can trust with every edition.

• LEADING PROBLEM-SCENARIO APPROACH HELPS STUDENT UNDERSTAND AND APPLY CONCEPTS. A hallmark strength of this text, this unique approach helps students understand statistical techniques within an applications setting. The statistical results provide insights into business decisions and detail how statistics are used within business today to solve problems.

• SYSTEMATIC APPROACH EMPHASIZES PROVEN METHODS AND APPLICATIONS. Students first develop a computational foundation and learn the use of techniques before moving to statistical application and interpretation of the value of techniques. Methods Exercises at the end of each section stress computation and use of formulas, while Application Exercises require students to use what they know about statistics to address real-world problems.

• CENGAGENOW ONLINE COURSE MANAGEMENT SYSTEM PROVIDES STUDENT RESULTS NOW! This robust, online course management system gives you more control in less time and delivers better student outcomes -- NOW. CengageNOW includes teaching and learning resources organized around lecturing, creating assignments, grading, quizzing, and tracking student progress and performance. Flexible assignments, automatic grading and a gradebook option provide more control while saving you valuable time. A Personalized Study diagnostic tool empowers students to master concepts, prepare for exams, and become more involved in class.

• USE OF CUMULATIVE STANDARD NORMAL DISTRIBUTION TABLE PREPARES STUDENTS TO WORK WITH STATISTICAL SOFTWARE. To more effectively prepare today's students to use computer software in statistics, this book incorporates a normal probability table that is consistent with today's statistical software. This cumulative normal probability table also makes it easier to compute p-values for hypothesis testing.

• SIMPLIFIED INTRODUCTION TO P-VALUES CLARIFIES UNDERSTANDING FOR STUDENTS. As in the previous edition, this edition emphasizes the use of p-values as the preferred approach to hypothesis testing. To further clarify the introduction of this concept for students, the authors now separate a simplified conceptual definition of p-values from operational definitions that clarify how the p-value is computed for a lower-tail test, an upper-tail test, and a two-tail test.

• STUDENTS LEARN TO USE SOFTWARE TO COMPUTE P-VALUES. For your flexibility, an optional appendix clearly demonstrates how to use MINITAB and Excel to compute p-values associated with z, t, and F test statistics. This coverage is particularly helpful when discussing hypothesis testing (Chs. 9-16).

David R. Anderson

Dennis J. Sweeney

Dennis J. Sweeney is Professor Emeritus of Quantitative Analysis and founder of the Center for Productivity Improvement at the University of Cincinnati. Born in Des Moines, Iowa, he earned a BSBA degree from Drake University and his MBA and DBA degrees from Indiana University, where he was an NDEA Fellow. Professor Sweeney has worked in the management science group at Procter & Gamble and has been a visiting professor at Duke University. Professor Sweeney served as Head of the Department of Quantitative Analysis and four years as Associate Dean of the College of Business Administration at the University of Cincinnati. Professor Sweeney has published more than 30 articles and monographs in the area of management science and statistics. The National Science Foundation, IBM, Procter & Gamble, Federated Department Stores, Kroger and Cincinnati Gas & Electric have funded his research, which has been published in Management Science, Operations Research, Mathematical Programming, Decision Sciences and other journals. Professor Sweeney has co-authored ten textbooks in the areas of statistics, management science, linear programming and production and operations management.

Thomas A. Williams

N/A

Jeffrey D. Camm

Dr. Jeffrey D. Camm is the Inmar Presidential Chair and Associate Dean of Business Analytics in the School of Business at Wake Forest University. Born in Cincinnati, Ohio, he holds a B.S. from Xavier University (Ohio) and a Ph.D. from Clemson University. Prior to joining the faculty at Wake Forest, he served on the faculty of the University of Cincinnati. He has also served as a visiting scholar at Stanford University and as a visiting Professor of Business Administration at the Tuck School of Business at Dartmouth College. Dr. Camm has published more than 40 papers in the general area of optimization applied to problems in operations management and marketing. He has published his research in numerous professional journals, including Science, Management Science, Operations Research and Interfaces. Dr. Camm was named the Dornoff Fellow of Teaching Excellence at the University of Cincinnati and he was the 2006 recipient of the INFORMS Prize for the Teaching of Operations Research Practice. A firm believer in practicing what he preaches, he has served as an operations research consultant to numerous companies and government agencies. From 2005 to 2010 he served as editor-in-chief of Interfaces. In 2016, Dr. Camm received the George E. Kimball Medal for service to the operations research profession and in 2017 he was named an INFORMS Fellow.

James J. Cochran

James J. Cochran is Associate Dean for Research, Professor of Applied Statistics and the Rogers-Spivey Faculty Fellow at The University of Alabama. Born in Dayton, Ohio, he earned his B.S., M.S., and M.B.A. from Wright State University and his Ph.D. from the University of Cincinnati. He has been at The University of Alabama since 2014 and has been a visiting scholar at Stanford University, Universidad de Talca, the University of South Africa and Pole Universitaire Leonard de Vinci. Dr. Cochran has published more than 40 papers in the development and application of operations research and statistical methods. He has published in several journals, including Management Science, The American Statistician, Communications in Statistics—Theory and Methods, Annals of Operations Research, European Journal of Operational Research, Journal of Combinatorial Optimization, Interfaces and Statistics and Probability Letters. He received the 2008 INFORMS Prize for the Teaching of Operations Research Practice, 2010 Mu Sigma Rho Statistical Education Award and 2016 Waller Distinguished Teaching Career Award from the American Statistical Association. Dr. Cochran was elected to the International Statistics Institute in 2005, was named a Fellow of the American Statistical Association in 2011 and was named a Fellow of INFORMS in 2017. He received the Founders Award in 2014, the Karl E. Peace Award in 2015 from the American Statistical Association and the INFORMS President’s Award in 2019. A strong advocate for effective operations research and statistics education as a means of improving the quality of applications to real problems, Dr. Cochran has chaired teaching effectiveness workshops around the globe. He has served as operations research consultant to numerous companies and not-for-profit organizations.

Preface.
1. Data and Statistics.
2. Descriptive Statistics: Tabular and Graphical Displays.
3. Descriptive Statistics: Numerical Measures.
4. Introduction to Probability.
5. Discrete Probability Distributions.
6. Continuous Probability Distributions.
7. Sampling and Sampling Distributions.
8. Interval Estimation.
9. Hypothesis Tests.
10. Inference about Means and Proportions with Two Populations.
12. Comparing Multiple Proportions, Test of Independence and Goodness of Fit.
13. Experimental Design and Analysis of Variance.
14. Simple Linear Regression.
15. Multiple Regression.
16. Regression Analysis: Model Building.
17. Time Series Analysis and Forecasting.
18. Nonparametric Methods.
19. Statistical Methods for Quality Control.
20. Index Numbers.
21. Decision Analysis.
22. Sample Survey (online).
Appendix A: References and Bibliography.
Appendix B: Tables.
Appendix C: Summation Notation.
Appendix D: Self-Test Solutions and Answers to Even –Numbered Exercises.
Appendix E: Microsoft Excel 2013 and Tools for Statistical Analysis.
Appendix F: Computing p-Values Using Minitab and Excel.
Index.

# New to this edition

• Descriptive Statistics--Chapters 2 and 3. We have significantly revised these chapters to incorporate new material on data visualization, best practices, and much more. Chapter 2 has been reorganized to include new material on side-by-side and stacked bar charts, and a new section has been added on data visualization and best practices I creating effective displays. Chapter 3 now includes coverage of the geometric mean in the section on measures of location. The geometric mean has many applications in the computation of growth rates for financial assets, annual percentage rates, and so on. Chapter 3 also includes a new section on data dashboards and how summary statistics can be incorporated to enhance their effectiveness.

# Supplements

All supplements have been updated in coordination with the Main title.
Please see Main title page for new to this edition information.

## Instructor Supplements

Instructor's Resource CD-ROM  (ISBN-10: 1285170881 | ISBN-13: 9781285170886)

Find all of the resources you need at your fingertips with this one-stop source for planning, teaching, grading, and assessments. This CD-ROM includes the author-written Solutions Manual, solutions to Case Problems, and the Microsoft PowerPint lecture slides. In addition, an accurate test bank and ExamView computerized testing software allow you to create, edit, store, and print paper exams, or offer online exams via the Internet.

Solutions Manual  (ISBN-10: 128517089X | ISBN-13: 9781285170893)

Prepared by the text's authors, the Solutions Manual includes solutions to all problems in the text and has been thoroughly updated to correspond with the newly revised twelfth edition. for your convenience, this edition shows the exercise solution steps using the cumulative normal distribution and offers more details about how to compute p-values. This Solutions Manual is available in printed form, on the IRCD, and in the password-protected section of the instructor website.

MindTap Business Statistics, 2 terms (12 months) Instant Access for Anderson/Sweeney/Williams/Camm/Cochran's Statistics for Business & Economics, Revised  (ISBN-10: 1305104854 | ISBN-13: 9781305104853)

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## Student Supplements

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MindTap Business Statistics, 2 terms (12 months) Instant Access for Anderson/Sweeney/Williams/Camm/Cochran's Statistics for Business & Economics  (ISBN-10: 1285513142 | ISBN-13: 9781285513140)

MindTap is a fully online, highly personalized learning experience built upon Cengage Learning content. MindTap combines student learning tools - readings, multimedia, activities and assessments - into a singular Learning Path that guides students through their course. Instructors personalize the experience by customizing authoritative Cengage Learning content and learning tools, including the ability to add their own content in the Learning Path via apps that integrate into the MindTap framework seamlessly with Learning Management Systems.

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MindTap is a fully online, highly personalized learning experience built upon Cengage Learning content. MindTap combines student learning tools - readings, multimedia, activities and assessments - into a singular Learning Path that guides students through their course. Instructors personalize the experience by customizing authoritative Cengage Learning content and learning tools, including the ability to add their own content in the Learning Path via apps that integrate into the MindTap framework seamlessly with Learning Management Systems.