An RSI Understanding Risk method
Probability distribution fitting
Probability distribution fitting is one of the methods used by Risk Sciences International to better understand risk.
Broadly
Probability distribution fitting involves identifying the statistical distribution that best represents a dataset’s variability. In risk analysis, this supports stochastic modeling, uncertainty analysis, and simulation. Selection must reflect the nature of the data—normal, log-normal, Poisson, etc.—and be validated with goodness-of-fit tests.
More specifically
RSI applies probability distribution fitting to support Monte Carlo simulations, reliability modeling, and uncertainty propagation. Its analysts validate assumptions using diagnostic plots and statistical criteria, ensuring that modeled variability accurately reflects real-world uncertainty. This method underpins RSI’s quantitative modeling strength.