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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.
- 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.
- 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.
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).