Business Analytics eBook, 3rd Edition

James R. Evans

Business Analytics eBook, 3rd Edition

By James R. Evans
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James R. Evans
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Business Analytics teaches the fundamental concepts of modern business analytics and provides vital tools in understanding how data analysis works in today’s organisations. Author James Evans takes a fair and comprehensive, approach, examining business analytics from both descriptive and predictive perspectives. Students learn how to apply basic principles, communicate with analytics professionals, and effectively use and interpret analytic models to make better business decisions. And included access to commercial grade analytics software gives students real-world experience and career-focused value. As such, the 3rd Edition has gone through an extensive revision and now relies solely on Excel, enhancing students’ skills in the program and basic understanding of fundamental concepts.

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Five sections guide students through the information
  • Part 1: Foundations of Business Analytics. The first two chapters provide the basic foundations needed to understand business analytics and Microsoft Excel, and show students how to manipulate data and develop simple spreadsheet models.
  • Part 2: Descriptive Analytics. Chapters 3 through 7 cover the fundamental tools and methods of data analysis and statistics. These chapters focus on visual representations of data, descriptive statistical measures, probability distributions and data modeling, sampling and estimation, and statistical inference.
  • Part 3: Predictive Analytics. Chapters 8 through 12 develop approaches for applying trendlines and regression analysis, forecasting and introductory data mining techniques, building and analysing models on spreadsheets, and simulation and risk analysis.
  • Part 4: Prescriptive Analytics. Chapters 13 and 14 explore linear, integer, and nonlinear optimisation models and applications. Chapter 15 focuses on what-if and sensitivity analysis in optimisation, and visualisation of Solver reports.
  • Part 5: Making Decisions. Chapter 16 focuses on philosophies, tools, and techniques of decision analysis.
Table of contents
  • 1. Introduction to Business Analytics
  • 2. Database Analytics
  • 3. Data Visualization
  • 4. Descriptive Statistics 
  • 5. Probability Distributions and Data Modeling
  • 6. Sampling and Estimation
  • 7. Statistical Inference
  • 8. Trendlines and Regression Analysis
  • 9. Forecasting Techniques
  • 10. Introduction to Data Mining
  • 11. Spreadsheet Modeling and Analysis
  • 12. Monte Carlo Simulation and Risk Analysis
  • 13. Linear Optimization
  • 14. Integer and Nonlinear Optimization
  • 15. Optimization Analytics
  • 16. Decision Analysis