Monte Carlo vs. Uncertainty Trees

Uncertainty analysis is a cornerstone of sound decision-making, yet analysts are often faced with a key question: which method is most appropriate for the problem at hand?

Two of the most widely used approaches, Monte Carlo simulation and Uncertainty Tree analysis, are powerful tools, but they serve different purposes and excel under different conditions.

In this webinar, we will explore the similarities and differences between Monte Carlo simulation and Uncertainty Tree analysis, with an emphasis on how each method represents uncertainty, models risk, and supports decision-making. Participants will learn the strengths, limitations, and practical applications of both techniques, along with clear criteria to help determine when one approach is more suitable than the other.

Through conceptual explanations and practical examples, we will examine how these methods are used in real-world analyses, highlighting common pitfalls and best practices. By the end of the session, attendees will have a stronger framework for selecting the right uncertainty analysis technique and improving the quality, credibility, and insight of their analytical work.

After registering, you will receive a confirmation email containing your webinar credentials.

Registration Link: https://attendee.gotowebinar.com/rt/40979253405363287