| Probability distributions are vital in Quantitative Risk Assessment (QRA) as they model uncertainties and estimate risks numerically. Different distributions apply to various risks—normal for natural variations, lognormal for skewed risks, exponential for failure times, and Poisson for rare events. Monte Carlo simulations use these distributions to run thousands of scenarios, helping predict extreme outcomes. Key metrics like expected loss, value at risk (VaR), and probability of failure (PoF) quantify risks. Widely used in finance, healthcare, engineering, and cybersecurity, probability distributions enable data-driven decision-making and better risk management. If you want to know more about Quantitative Risk Assessment, then you can visit on our site.
https://www.sigma-hse.co.in/quantitative-risk-assessment-qra
|
