An RSI Understanding Risk method
Uncertainty propagation modeling
Uncertainty propagation modeling is one of the methods used by Risk Sciences International to better understand risk.
Broadly
Uncertainty propagation modeling quantifies how input uncertainty affects model outputs. It typically uses Monte Carlo simulation or bootstrapping to simulate thousands of iterations, generating distributions of possible outcomes. This enhances understanding of confidence, risk tolerance, and decision robustness. However, it requires well-characterized inputs and computational capacity.
More specifically
RSI applies uncertainty propagation in its probabilistic risk models, supporting transparency and insight into the range and likelihood of possible results. RSI carefully documents input distributions, validates outputs, and interprets findings for decision contexts. The method helps RSI clients weigh risk-based decisions with a fuller appreciation of possible variation and confidence.