If you have attended HDR’s Calibrated Probability Assessments course and thought your team or organization would benefit from that skill, this is your opportunity. During Advanced Calibration Methods, you will learn how to deliver your own calibration training, compute performance weights for your experts, and eliminate inconsistency from expert estimates. If you are not already registered in the course please click here.
Learn how to run your own calibration sessions for your organization.
Calibrated Probability Assessments
- CBT Modules: 3 (approx. 1 hr)
- Live Workshop: 1
- Audit of one calibration workshop presented by the participant
- Spreadsheets for administering tests and recording scores
- Tools for computing performance weights and eliminating expert inconsistency
- PDF copy of PowerPoint slides
Recommended Next Courses
Creating Simulations in Excel Basic and Intermediate, Making Decisions Under Uncertainty, Measurement Methods in Excel Basic and Intermediate
Douglas Hubbard is the inventor of the Applied Information Economics (AIE) method and founder of Hubbard Decision Research (HDR). He is the author of How to Measure Anything: Finding the Value of Intangibles in Business, The Failure of Risk Management: Why It’s Broken and How to Fix It, Pulse: The New Science of Harnessing Internet Buzz to Track Threats and Opportunities and his latest book, How to Measure Anything in Cybersecurity Risk (Wiley, 2016). He has sold over 100,000 copies of his books in eight different languages. Two of his books are required reading for the Society of Actuaries exam prep. In addition to his books, Mr. Hubbard has been published in several periodicals including Nature, The IBM Journal of Research and Development, OR/MS Today, Analytics, CIO, Information Week, and Architecture Boston.
Use the form on the right to register for your live workshop. Each workshop is two hours long and can be completed at any time before or after completion of the CBT modules.
During the live workshop, you will:
- Review Q&A for delivering your own calibration training.
- Discuss in more detail methods for aggregating experts that outperform simply averaging responses.
- See a hands-on example of methods for further reducing expert inconsistency.