Which type of risk analysis focuses on numerical and statistical data?

Quantitative risk analysis is the methodology that emphasizes numerical and statistical data to assess risks. This approach involves utilizing mathematical models to estimate the likelihood of specific risks and their potential impact on a project or organization. By assessing risks in quantitative terms, analysts can provide concrete figures that help in decision-making and prioritizing risk management strategies.

In quantitative risk analysis, techniques such as simulations, statistical modeling, and probability distributions are often employed to analyze risks. This allows stakeholders to see not only the potential outcomes but also the range of possible impacts, which can enhance planning and resource allocation.

The focus on numerical data differentiates quantitative risk analysis from other types of approaches. For example, qualitative risk analysis relies more on subjective judgment and categorization of risks, rather than concrete numerical assessments. Cumulative and comparative risk analyses also do not inherently focus on numerical data in the same way, making quantitative risk analysis distinct in its reliance on statistical methods to provide a thorough risk evaluation.