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Course Description

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.

You are required to have completed the following courses or have equivalent experience before taking this course:

  • Understanding and Visualizing Data
  • Implementing Scientific Decision Making
  • Using Predictive Data Analysis

Faculty Author

Chris Anderson

Benefits to the Learner

  • 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

Target Audience

  • Analysts
  • Functional Managers
  • Executives
  • Consultants
  • Any professional that uses data to make business decisions

Accrediting Associations

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The Hotel School
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