Business Analytics

Wayne L. Winston is Professor Emeritus of Decision Sciences at the Kelley School of Business at Indiana University and is now Professor of Decision and Information Sciences at the Bauer College at the University of Houston. Dr. Winston has received more than 45 teaching awards and is a six-time recipient of the school-wide M.B.A. award. His current interest focuses on showing how to use spreadsheet models to solve business problems in all disciplines, particularly in finance, sports and marketing. In addition to publishing more than 20 articles in leading journals, Dr. Winston has written successful textbooks on topics including operations research, mathematical programming, simulation modeling, spreadsheet modeling, data analysis for managers, marketing analytics and more. Dr. Winston received his B.S. degree in mathematics from MIT and his Ph.D. in operations research from Yale. S. Christian Albright received both his B.S. degree in mathematics and his Ph.D. in operations research from Stanford University. He then taught in the Operations and Decision Technologies Department in the Kelley School of Business at Indiana University until his retirement in 2011. He has taught courses in management science, computer simulation and statistics to all levels of business students, including undergraduate, M.B.A. and Ph.D. students. He has published more than 20 articles in leading operations research journals in applied probability. After retiring, he worked for several years for the Palisade Software Company and is the author of several successful textbooks.

1. Introduction to Business Analytics.
Part 1: EXPLORING DATA.
2. Describing the Distribution of a Single Variable.
3. Finding Relationships among Variables.
Part 2: PROBABILITY AND DECISION MAKING UNDER UNCERTAINTY.
4. Probability and Probability Distributions.
5. Normal, Binomial, Poisson, and Exponential Distributions.
6. Decision Making under Uncertainty.
Part 3: STATISTICAL INFERENCE.
7. Sampling and Sampling Distributions.
8. Confidence Interval Estimation.
9. Hypothesis Testing.
Part 4: REGRESSION ANALYSIS AND TIME SERIES FORECASTING.
10. Regression Analysis: Estimating Relationships.
11. Regression Analysis: Statistical Inference.
12. Time Series Analysis and Forecasting.
Part 5: OPTIMIZATION AND SIMULATION MODELING.
13. Introduction to Optimization Modeling.
14. Optimization Models.
15. Introduction to Simulation Modeling.
16. Simulation Models.
Part 6: ADVANCED DATA ANALYSIS.
17. Data Mining.
Part 7: BONUS ONLINE MATERIAL.
18. Importing Data into Excel.
19. Analysis of Variance and Experimental Design.
20. Statistical Process Control.
Appendix A: Statistical Reporting.