People Innovation Excellence

BUSINESS ANALYTICS (2/2 Credits)

Learning Outcomes:

On successful completion of this course, students will be able to: explain the motivations, concepts, methods, and methodologies for different types of analytics; identify the fundamental tools and methods of data analysis and statistics for descriptive analytics; practice several approaches for predictive analytics including: trendlines and regression analysis, forecasting, introductory data mining techniques, building and analyzing models on spreadsheets, simulation a; practice several approaches for prescriptive analytics including: linear, integer, nonlinear optimization models and applications.

Topics:

  1. Introduction to Business Analytics;
  2. Database Analytics;
  3. Descriptive Statistics;
  4. Probability Distributions and Data Modeling;
  5. Statistical Inference;
  6. Trendlines and Regression Analysis;
  7. Forecasting Techniques;
  8. Spreadsheet Modeling and Analysis;
  9. Simulation and Risk Analysis;
  10. Linear Optimization;
  11. Integer and Nonlinear Optimization;
  12. Optimization Analytics;
  13. Decision Analysis;
  14. Database Analytics;
  15. Probability Distributions and Data Modeling;
  16. Trendlines and Regression Analysis;
  17. Spreadsheet Modeling and Analysis;
  18. Linear Optimization;
  19. Decision Analysis;
  20. Explore the Spotfire Interface and Data Filters;
  21. Loading Data;
  22. Using Bar Charts;
  23. Scatter Plots;
  24. Trellising and Binning;
  25. Using Line Charts;
  26. Relative Comparisons;
  27. Using Tables;
  28. Tool Tips and Marking;
  29. Merging Multiple Data Tables;
  30. Relationships and Aggregation.

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