Decision Making Under Uncertainty: Introduction to Structured Expert Judgment

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Free Online Course: Decision Making Under Uncertainty: Introduction to Structured Expert Judgment provided by edX is a comprehensive online course, which lasts for 6 weeks long, 4-6 hours a week. The course is taught in English and is free of charge. Decision Making Under Uncertainty: Introduction to Structured Expert Judgment is taught by Tina Nane.

Overview
  • In an increasingly data-driven world, data and its use aren't always all it's cracked up to be. This course aims to explain how expert opinion can help in many areas where complex decisions need to be made.

    For instance, how can you predict volcano activity when no eruptions have been recorded over a long period of time? Or how can you predict how many people will be resistant to antibiotics in a country where there is no available data at national level? Or how about estimating the time needed to evacuate people in flood risk areas?

    In situations like these, expert opinions are needed to address complex decision-making problems. This course will show you the basics of various techniques that use expert opinion for uncertainty quantification. These techniques vary from the informal and undocumented opinion of one expert to a fully documented and formal elicitation of a panel of experts, such as the Classical Model (CM) or Cooke's method, which is arguably the most rigorous method for performing Structured Expert Judgment.

    CM, developed at TU Delft by Roger Cooke, has been successfully applied for over 30 years in areas as diverse as climate change, disaster management, epidemiology, public and global health, ecology, aeronautics/aerospace, nuclear safety, environment and ecology, engineering and many others.

Syllabus
  • WEEK 1: Why and when to use SEJ?

    WEEK 2: Statistical accuracy (calibration) and information score

    WEEK 3: Performance-based weights and the Decision Maker

    WEEK 4: Data analysis

    WEEK 5: Applications of CM

    WEEK 6: Practical matters (biases, experts, elicitation)