Which of the following is a key component of quantitative risk analysis?

Statistical modeling serves as a crucial component of quantitative risk analysis because it allows analysts to quantify potential risks using mathematical and statistical techniques. By applying statistical models, analysts can assess the likelihood of various risks and understand their potential impact on a project's objectives.

In quantitative risk analysis, statistical methods—such as simulations, probability distributions, and sensitivity analysis—enable analysts to make informed predictions based on data and historical trends. This quantitative approach provides a more objective foundation for decision-making compared to qualitative methods, which may rely on subjective judgment and rankings.

For effective risk management, understanding the probabilities and potential impacts of risks through statistical modeling is essential. This approach helps organizations allocate resources appropriately and develop strategies to mitigate or avoid significant risks, ultimately leading to more informed and strategic project management.