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New!

Business Analytics, 6th Edition

Jeffrey D. Camm, James J. Cochran, Michael J. Fry, Jeffrey W. Ohlmann

  • Copyright 2027
  • {{checkPublicationMessage('Published', '2026-01-01T00:00:00+0000')}}
Starting At $77.95 See pricing and ISBN options
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Business Analytics 6th Edition by Jeffrey D. Camm/James J. Cochran/Michael J. Fry/Jeffrey W. Ohlmann
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Overview

Present the full range of analytics -- from descriptive and predictive to prescriptive analytics to generative AI -- with Camm/Cochran/Fry/Ohlmann's market-leading "Business Analytics," 6th Edition. Step-by-step instructions teach students how to use Excel, Tableau, Power BI, R and Python to solve advanced analytics concepts. Choose your preferred software for teaching concepts. Solutions to problems and cases save grading time and provide students with practice. Updates cover topics beyond the traditional quantitative concepts such as data wrangling, data visualization, machine learning and AI, which are increasingly important in today's analytical problem solving. MindTap and WebAssign customizable online learning platforms offer an interactive eBook, auto-graded exercises, algorithmic practice problems and Exploring Analytics visualizations to strengthen students' understanding.

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Meet the Authors

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Jeffrey D. Camm

Jeffrey D. Camm is the Inmar Presidential Chair of Analytics and Senior Associate Dean for Faculty 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, Dr. Camm 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 Science, Management Science, Operations Research, The INFORMS Journal on Applied Analytics and other professional journals. Dr. Camm was named the Dornoff Fellow of Teaching Excellence at the University of Cincinnati and he was the recipient of the 2006 INFORMS Prize for the Teaching of Operations Research Practice. A firm believer in practicing what he preaches, he has served as a consultant to numerous companies and government agencies. Dr. Camm served as editor-in-chief of INFORMS Journal on Applied Analytics and is an INFORMS fellow.

James J. Cochran

James J. Cochran is Professor of Applied Statistics, the Mike and Cathy Mouron Research Chair and Associate Dean for Faculty and Research at the University of Alabama. Born in Dayton, Ohio, he earned his B.S., M.S. and M.B.A. degrees from Wright State University and his Ph.D. from the University of Cincinnati. Dr. Cochran has served 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 50 papers in the development and application of operations research and statistical methods. He has published his research in 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. He was the 2008 recipient of the INFORMS Prize for the Teaching of Operations Research Practice and the 2010 recipient of the Mu Sigma Rho Statistical Education Award. He received the Founders Award in 2014 and the Karl E. Peace Award in 2015 from the American Statistical Association. In 2017 he received the American Statistical Association’s Waller Distinguished Teaching Career Award and in 2018 he received the INFORMS President’s Award. Dr. Cochran is an elected member of the International Statistics Institute, a fellow of the American Statistical Association and a fellow of INFORMS. A strong advocate for effective statistics and operations research education as a means of improving the quality of applications to real problems, Dr. Cochran has organized and chaired teaching workshops throughout the world.

Michael J. Fry

Michael J. Fry is Professor of Operations, Business Analytics and Information Systems, Lindner Research Fellow and Managing Director of the Center for Business Analytics in the Carl H. Lindner College of Business at the University of Cincinnati. Born in Killeen, Texas, he earned a B.S. from Texas A&M University and his M.S.E. and Ph.D. 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 a visiting professor at Cornell University and the University of British Columbia. Dr. Fry has published more than 25 research papers in journals such as Operations Research, M&SOM, Transportation Science, Naval Research Logistics, IISE Transactions, Critical Care Medicine and INFORMS Journal on Applied Analytics. 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 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 and Botanical Garden. Dr. Fry 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 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 his M.S. and Ph.D. from the University of Michigan. He has been at the University of Iowa since 2003. Dr. Ohlmann’s research on the modeling and solution of decision-making problems has produced more than two dozen research papers in journals such as Operations Research, Mathematics of Operations Research, INFORMS Journal on Computing, Transportation Science, the European Journal of Operational Research and INFORMS Journal on Applied Analytics (formerly Interfaces). He has collaborated with companies such as Transfreight, LeanCor, Cargill, the Hamilton County Board of Elections as well as three National Football League franchises. Because of the relevance of his work to industry, he was bestowed the George B. Dantzig Dissertation Award and was recognized as a finalist for the Daniel H. Wagner Prize for Excellence in Operations Research Practice.

What's New

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  • Explore AI’s impact with a new chapter on generative models, real-world use cases, ethics, hands-on tools and assignments, helping students build future-ready skills.
  • New Python appendices using Google Colab offer flexible, hands-on analytics tools and practice problems -- no installs needed -- to expand learning across platforms.
  • Over 200 new end-of-chapter problems, now labeled Conceptual or Application, with software-specific problems for R, Python or Orange in chapters cover machine learning.
  • New Power BI appendix for Data Visualization includes step-by-step directions and examples on how to use Power BI to import data and create key charts from the chapter.
  • Domain area labels have been added to all problems and cases to help instructors and students identify which field (business, healthcare, government) is featured.

Features

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  • Practical, relevant problems across functional business areas provide ample practice opportunities at various difficulty levels, helping students master concepts and skills.
  • Analytics in Action features in each chapter show how professionals use analytics in real-world settings across healthcare, finance, marketing and manufacturing.
  • Online DATAfiles and MODELfiles save time, offering downloadable data, Excel models and R/Python scripts for hands-on practice with machine learning tools.

Table of Contents

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1. Introduction.
2. Descriptive Statistics.
3. Data Visualization.
4. Data Wrangling.
5. Probability: An Introduction to Modeling Uncertainty.
6. Unsupervised Machine Learning.
7. Statistical Inference.
8. Linear Regression.
9. Time Series Analysis and Forecasting.
10. Supervised Machine Learning: Regression.
11. Supervised Machine Learning: Classification.
12. Spreadsheet Modeling.
13. Monte Carlo Simulation.
14. Linear Optimization Models.
15. Integer Linear Optimization Models.
16. Nonlinear Optimization Models.
17. Decision Analysis.
18. Artificial Intelligence.
Appendix A: Basics of Excel.
Appendix B: Database Basics with Microsoft Access.
Appendix C: Solutions to Even-Numbered Questions (Cengage eBook).
Appendix D: Microsoft Excel Online and Tools for Statistical Analysis (Cengage eBook).

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Each MindTap product offers the full, mobile-ready textbook combined with superior and proven learning tools at one affordable price. Students who purchase digital access can add a print option at any time when a print option is available for their course.

This Cengage solution can be seamlessly integrated into most Learning Management Systems (Blackboard, Brightspace by D2L, Canvas, Moodle, and more) but does require a different ISBN for access codes. Please work with your Cengage Learning Consultant to ensure the proper course set up and ordering information. For additional information, please visit the LMS Integration site.

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  • ISBN-10: 821405737X
  • ISBN-13: 9798214057378
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  • ISBN-10: 8214057396
  • ISBN-13: 9798214057392
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Traditional eBook and Print Options

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  • ISBN-10: 8214057515
  • ISBN-13: 9798214057514
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  • ISBN-10: 8214057361
  • ISBN-13: 9798214057361
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Supplements

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Cengage provides a range of supplements that are updated in coordination with the main title selection. For more information about these supplements, contact your Learning Consultant.

FOR STUDENTS

MindTap for Camm/Cochran/Fry/Ohlmann's Business Analytics, 1 term Instant Access

ISBN: 9798214057378
MindTap for "Business Analytics" is designed to develop students' decision-making skills. Students develop and hone essential career skills and experience with: Excel Activities -- algorithmic problems based on end-of-chapter problems from the book that provide students with an authentic experience solving problems using spreadsheets. These problems are integrated directly in MindTap and provide students with real-time feedback on their answers with contextual support directly from Office Online, system generated Excel solution files and video walk-throughs of a similar problem prepared by the text authors. Exploring Analytics Videos & Applets -- videos that explain fundamental statistical concepts and interactive, visual demonstrations that allow students to manipulate and experiment with topics from the chapter. Bongo Videos -- AI graded videos that help students develop their presentation skills and story telling skills by providing them instant feedback on presentation skills (speaking rate, use of filler words, eye contact, etc…) and on their ability to present analytical content in an understandable way.

MindTap for Camm/Cochran/Fry/Ohlmann's Business Analytics, 2 terms Instant Access

ISBN: 9798214057392
MindTap for "Business Analytics" is designed to develop students' decision-making skills. Students develop and hone essential career skills and experience with: Excel Activities -- algorithmic problems based on end-of-chapter problems from the book that provide students with an authentic experience solving problems using spreadsheets. These problems are integrated directly in MindTap and provide students with real-time feedback on their answers with contextual support directly from Office Online, system generated Excel solution files and video walk-throughs of a similar problem prepared by the text authors. Exploring Analytics Videos & Applets -- videos that explain fundamental statistical concepts and interactive, visual demonstrations that allow students to manipulate and experiment with topics from the chapter. Bongo Videos -- AI graded videos that help students develop their presentation skills and story telling skills by providing them instant feedback on presentation skills (speaking rate, use of filler words, eye contact, etc…) and on their ability to present analytical content in an understandable way.