Who should attend
- Functional Managers
- Any professional that uses data to make business decisions
About the course
Decision making is never as simple as we would like it to be, since rarely does a single factor alone predict an outcome. In a competitive business environment, not taking this uncertainty into account has serious costs. In this course, you'll use foundations in probability to describe risk mathematically and incorporate those calculations into your decisions so you can take them to the next level. Working through increasingly complex modeling situations, you will learn to use estimates of probable future outcomes for Go/No-Go decisions and to run a Monte Carlo simulation allowing you to examine outcomes that vary based on multiple, interdependent decisions.
The courses Understanding and Visualizing Data, Implementing Scientific Decision Making, and Using Predictive Data Analysis are required to be completed prior to starting this course.
KEY COURSE TAKEAWAYS
- Calculate marginal value for a binary decision
- Determine optimal values for a repeating, sequential decision
- Build risk aversion into your model
- Calculate utility for a given decision
- Develop and use a Monte Carlo simulation
- Perform sensitivity analysis Use expected utility to accommodate risk
Chris K Anderson is a Professor at the Cornell School of Hotel Administration. Prior to his appointment in 2006, he was on faculty at the Ivey School of Business in London, Ontario Canada. His main research focus is on revenue management and service pricing. He actively works with industry, acros...
Read more about Business Analytics
Because of COVID-19, many providers are cancelling or postponing in-person programs or providing online participation options.
We are happy to help you find a suitable online alternative.