
Business Analytics
South-Western College Publishing
6th Edition
Published on 1. January 2026
Book
Paperback/Softback
1050 pages
979-8-214-05736-1 (ISBN)
Description
Develop analytical skills that are in high demand with Camm/Cochran/Fry/Ohlmann's 'Business Analytics,' 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.
More details
Edition
6th edition
Language
English
Place of publication
Florence
United States
Publishing group
Cengage Learning, Inc
Target group
College/higher education
Product notice
Paperback (trade)
Unsewn / adhesive bound
Dimensions
Height: 274 mm
Width: 214 mm
Thickness: 43 mm
Weight
2400 gr
ISBN-13
979-8-214-05736-1 (9798214057361)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
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.
Content
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).