Modern Business Statistics with Microsoft® Excel®,
8th Edition

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. Statistical Inferences About Means and Proportions with Two Populations.
11. Inferences About Population Variances.
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. Decision Analysis.
21. Sample Survey.
Appendix A: References and Bibliography.
Appendix B: Tables.
Appendix C: Summation Notation.
Appendix D: Microsoft Excel and Tools for Statistical Analysis.
Appendix E: Microsoft Excel Online and Tools for Statistical Analysis. (Cengage eBook only)
Appendix F: Solutions to Even-Numbered Exercises. (Cengage eBook only)

• Jeffrey D. Camm

  Jeffrey D. Camm is the Inmar Presidential Chair and senior associate dean of business analytics programs 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 been a visiting scholar at Stanford University and a visiting professor of business administration at the Tuck School of Business at Dartmouth College. Dr. Camm has published more than 45 papers in the general area of optimization applied to problems in operations management and marketing. He has published his research in many professional journals, including Science, Management Science, Operations Research and the INFORMS Journal on Applied Analytics. 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, Dr. Camm has served as an operations research consultant to numerous companies and government agencies. From 2005 to 2010 he served as editor-in-chief of the INFORMS Journal on Applied Analytics (formerly 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, a 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 served as 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 50 papers in the development and application of operations research and statistical methods. He has published in numerous 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, INFORMS Journal on Applied Analytics, BMJ Global Health and Statistics and Probability Letters. Dr. Cochran received the 2008 INFORMS prize for the Teaching of Operations Research Practice, the 2010 Mu Sigma Rho Statistical Education Award and the 2016 Waller Distinguished Teaching Career Award from the American Statistical Association. Dr. Cochran was elected to the International Statistics Institute in 2005 and was named a fellow of the American Statistical Association in 2011 and a fellow of INFORMS in 2017. He also received the Founders Award in 2014 and the Karl E. Peace Award in 2015 from the American Statistical Association. In addition, he received 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 also served as an operations research or statistics consultant to numerous companies and not-for-profit organizations.

• Michael J. Fry

  Michael J. Fry is a professor of operations, business analytics and information systems as well as academic director of the Center for Business Analytics in the Carl H. Lindner College of Business at the University of Cincinnati. Born in Killeen, Texas, Dr. Fry earned his B.S. from Texas A&M University and M.S.E. and Ph.D. degrees from the University of Michigan. He has been at the University of Cincinnati since 2002, where he was previously department head. He has also been named a Lindner Research Fellow. Dr. Fry has also been a visiting professor at the Samuel Curtis Johnson Graduate School of Management at Cornell University and the Sauder School of Business at the University of British Columbia.He has published more than 25 research papers in journals such as Operations Research, M&SOM, Transportation Science, Naval Research Logistics, IIE Transactions, Critical Care Medicine and Interfaces. His research interests are in applying quantitative management methods to the areas of supply chain analytics, sports analytics and public-policy operations. He has worked with many different organizations for his research, including Dell, Inc., Starbucks Coffee Company, Great American Insurance Group, the Cincinnati Fire Department, the State of Ohio Election Commission, the Cincinnati Bengals and the Cincinnati Zoo & Botanical Garden. He was named a finalist for the Daniel H. Wagner Prize for Excellence in Operations Research Practice, and he has been recognized for both his research and teaching excellence at the University of Cincinnati.

• Jeffrey W. Ohlmann

  Jeffrey W. Ohlmann is associate professor of business analytics and a Huneke Research Fellow in the Tippie College of Business at the University of Iowa. Born in Valentine, Nebraska, he earned a B.S. from the University of Nebraska and M.S. and Ph.D. degrees from the University of Michigan. Dr. Ohlmann has been at the University of Iowa since 2003. His research on the modeling and solution of decision-making problems has produced more than two dozen research papers published in journals such as Operations Research, Mathematics of Operations Research, INFORMS Journal on Computing, Transportation Science and the European Journal of Operational Research. He has collaborated with organizations such as Transfreight, LeanCor, Cargill, the Hamilton County Board of Elections and three National Football League franchises. Because of the relevance of his work to industry, Dr. Ohlmann received the George B. Dantzig Dissertation Award, and he was recognized as a finalist for the Daniel H. Wagner Prize for Excellence in Operations Research Practice.

• David R. Anderson

  David R. Anderson is a leading author and professor emeritus of quantitative analysis in the College of Business Administration at the University of Cincinnati. Dr. Anderson has served as head of the Department of Quantitative Analysis and Operations Management and as associate dean of the College of Business Administration. He was also coordinator of the college’s first executive program. In addition to introductory statistics for business students, Dr. Anderson taught graduate-level courses in regression analysis, multivariate analysis and management science. He also taught statistical courses at the Department of Labor in Washington, D.C. Dr. Anderson has received numerous honors for excellence in teaching and service to student organizations. He is the co-author of ten well-respected textbooks related to decision sciences, and he actively consults with businesses in the areas of sampling and statistical methods. Born in Grand Forks, North Dakota, Dr. Anderson earned his B.S., M.S. and Ph.D. degrees from Purdue University.

• 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 B.S.B.A. degree from Drake University and his M.B.A. and D.B.A. degrees from Indiana University, where he was an NDEA fellow. Dr. Sweeney has worked in the management science group at Procter & Gamble and has been a visiting professor at Duke University. He also served as head of the Department of Quantitative Analysis and served four years as associate dean of the College of Business Administration at the University of Cincinnati. Dr. 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 journals such as Management Science, Operations Research, Mathematical Programming and Decision Sciences. Dr. 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

• Expanded Coverage of Data Visualization. This edition brings expanded coverage of data visualization concepts and tools in Chapter 2. A new section covers the visualization of geospatial data using maps. Introduce both choropleth maps and cartograms, while explaining how to create choropleth maps in Excel with this text. An expanded discussion of the use of data-ink ratio and decluttering to create effective visualizations has been added to existing coverage of best practices for data visualization.

• Extended Discussion of Regression Modeling. Chapter 16 is slightly reorganized to elaborated on key topics. A discussion was added about about comparing a regression model with a transformed dependent variable to a regression model using the untransformed dependent variable in the original units. A new example to illustrate the use of the Durbin-Watson statistic to test the presence of first-order autocorrelation has also been added.

• New Examples and Exercises Based on Real Data. This edition brings over 90 new examples and exercises based on real data and referenced sources. By using data from sources also used by The Wall Street Journal, USA Today, The Financial Times, Forbes and others, this text develops explanations and creates exercises that demonstrate the many uses of statistics in business and economics. Use real data from interesting and relevant problems to generate greater student interest in the material and enable the student to more effectively learn about both statistical methodology and its application.

• Case Problems. Four new case problems added to this edition. The 49 case problems in the text provide students with the opportunity to analyze somewhat larger data sets and prepare managerial reports based on the results of their analysis.

• Learning Objectives. New Learning Objectives (LOs) have been added to the beginning of each chapter. These LOs explain the key concepts that are covered in each chapter. The LOs are also mapped on to each problem so instructors can easily identify which LOs are covered by each problem.

• MINDTAP COMPLETE DIGITAL SOLUTION FEATURES EXCEL ONLINE INTEGRATION POWERED BY MICROSOFT®. MindTap allows students to actively engage in critical-thinking applications and learn valuable software skills for future careers. MindTap is an online learning platform that includes an interactive eBook and auto-graded, algorithmic exercises from the latest edition of the printed text. Over 100 Excel Online activities detail how to apply statistical problem-solving with real, live applications as they would on the job, using step-by-step problem walk-through videos and personalized Excel solutions.

• POWERFUL EXAMPLES AND EXERCISES MAKE CONCEPTS REAL AND MEMORABLE FOR STUDENTS. This acclaimed author team is known for creating exceptional exercises and examples that are strengthened with real data from sources such as the Census Bureau and The Wall Street Journal. Exercises drawn from real events encourage students to learn the statistical methodology and apply real data to problems. Approximately 90 new or updated examples and exercises now add to this edition's more than 1000 exercises.

• PROVEN EXERCISES ENSURE STUDENT UNDERSTANDING: Completely worked-out solutions for specific exercises appear in an appendix at the end of this edition. Students can complete the exercises and immediately check their solutions to evaluate their understanding of the concepts presented in each chapter.

• "STATISTICS IN PRACTICE" CHAPTER OPENERS IMMEDIATELY EMPHASIZE THE PRACTICAL VALUE OF INFORMATION STUDENTS ARE LEARNING. "Statistics in Practice" chapter openers highlight intriguing scenarios from companies such as Citibank and Procter & Gamble and clearly demonstrate the value of statistics in everyday business situations. These high-interest openers immediately draw students into the chapter information that follows.

• THIS EDITION PROVIDES BALANCED EMPHASIS ON METHODS AND APPLICATIONS. This experienced author team strikes an appropriate balance in methodology and application. Methods Exercises at the end of each section require students to use formulas and make necessary computations, while practical Application Exercises ask students to apply the chapter material to address real-world problems. Both the Methods and the Applications Exercises now include notations indicating which learning objectives are covered in each exercise.

• TRUSTED TEAM OF EXPERT AUTHORS ENSURE QUALITY, PRACTICALLY FOCUSED PRESENTATION. As respected leaders and active consultants in the fields of business and statistics, this acclaimed team of authors -- Camm, Cochran, Fry, Ohlmann, Anderson, Sweeney and Williams -- provide an accurate presentation of statistical concepts with every edition. They use their teaching experience to provide a cohesive, student-friendly writing approach. To ensure accuracy, the authors personally triple-check all problems and examples.

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