Business Analytics : Theory and Practice (Hardcover)

1. Introduction

2. Discrete and Continuous Probability Distributions

3. Introduction to R Software

4. Introduction to Python and XLSTAT

5. Basic Statistics

6. Sampling and ANOVA

7. Multivariate Probability Distribution

8. Regression

9. Path Model and Discriminant Analysis

10. PCA and Factor Analysis

11. Structural Equation Modelling

12. Moving Average and Box-Jenkin’s Method

13. Time Series Models Part II

14. Mathematical Optimization Techniques

15. Dynamic Programming, Markov Analysis, and Information Theory?

16. Nonlinear Optimization

17. Nature-Based Techniques and Multicriteria Decision Analysis Techniques

18. Artificial Neural Network

19. Learning Rules

20. Descriptive Analytics

21. Decision Tree?

22. Other Learning Techniques?

23. Simulation

24. Continuous Simulation

25. Simulation Optimization

26. Data Mining and Partitioning

27. Visualization Techniques and Dimension Reduction Techniques

28. Performance Metrics

29. Additional Techniques for Diagnostic Analytics and Prescriptive Analytics

30. Implementation of Different Methodologies with R