Business Analytics, Cengage International Edition, 6th Edition

Business Analytics, Cengage International Edition book cover

Business Analytics, Cengage International Edition

Author(s): Jeffrey Camm (Author), James Cochran (Author), Michael Fry (Author), Jeffrey Ohlmann (Author)

  • Publisher finelybook 出版社: South-Western College Pub
  • Publication Date 出版日期: 9 Mar. 2026
  • Edition 版本: 6th
  • Language 语言: English
  • Print length 页数: 1050 pages
  • ASIN: B0FQ2M6WJR
  • ISBN-13: 9798214505121

Book Description

Develop analytical skills that are in high demand with Camm/Cochran/Fry/Ohlmann’s “Business Analytics, Cengage International Edition” 6th Edition. Master the full range of analytics as you strengthen descriptive, predictive and prescriptive analytic skills, data visualization, unsupervised and supervised machine learning and generative AI. Examples and visuals illustrate data and results. Step-by-step instructions guide you through using Excel, Tableau, R , Power BI or Python (including the Python-based Orange software). Practical problems at all levels of difficulty let you apply what you’ve learned. Updates address topics beyond traditional quantitative concepts such as data wrangling, data visualization, machine learning and generative AI. MindTap and WebAssign online learning platforms are available with an interactive eBook, algorithmic practice problems and Exploring Analytics visualizations.

Editorial Reviews

Product description

About the Author

Jeffrey D. Camm is professor and Inmar Presidential Chair in analytics in the School of Business at Wake Forest University. Born in Cincinnati, Ohio, he holds a BS from Xavier University (Ohio) and a Ph.D. from Clemson University. Prior to joining the faculty at Wake Forest, he was 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 over 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, 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. He is a recipient of the George E. Kimball Medal for service to the operations research profession. 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 INFORMS Journal on Applied Analytics. In 2017, he was named an INFORMS Fellow. In 2021, Professor Camm was named an Academic Data Leader by Chief Data Officer (CDO) Magazine.

James J. Cochran is professor of applied statistics and the Mike and Kathy Moroun Research Chair at the University of Alabama. Born in Dayton, Ohio, he earned his BS, MS and MBA degrees 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. Professor Cochran has published over 60 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, Statistics and Probability Letters and other professional Journals. Professor Cochran’s research has been funded by the Department of Justice, National Science Foundation and other agencies. 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. Professor Cochran was elected to the International Statistics Institute in 2005 and named a Fellow of the American Statistical Association in 2011. 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 was named a Fellow of INFORMS; in 2018, he received the INFORMS President’s Award; in 2024, he received the William G. Hunter Award from the American Society for Quality and in 2025, he was named a Fellow of the African Academy of Sciences. He has been recognized as a finalist for the Innovative Applications in Analytics Award three times.

Michael J. Fry is professor of operations, business analytics and information systems and senior director of Centers and Institutes in the Carl H. Lindner College of Business at the University of Cincinnati. Born in Killeen, Texas, he earned a BS from Texas A&M University and MSE 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, director of the Center for Business Analytics and has been named a Lindner Research Fellow. He 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. Professor Fry has published 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 has been funded by the National Science Foundation and other funding agencies. 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. In 2024, Professor Fry was named an Academic Data Leader by Chief Data Officer (CDO) Magazine.

Jeffrey W. Ohlmann is associate professor of management sciences and Huneke Research Fellow in the Tippie College of Business at the University of Iowa. Born in Valentine, Nebraska, he earned a BS from the University of Nebraska, and MS and Ph.D. degrees from the University of Michigan. He has been at the University of Iowa since 2003. Professor 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. He has collaborated with companies 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, 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.

Table of Contents
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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