According to the PMBOK® Guide, specifically within the Perform Quantitative Risk Analysis process, numerical analysis is performed on the combined effect of identified individual project risks and other sources of uncertainty on overall project objectives.

Sensitivity Analysis: This is a quantitative technique used to determine which individual project risks or other sources of uncertainty have the most potential impact on project outcomes. It helps to correlate the variations in project outcomes with variations in elements of the quantitative risk model.

Tornado Diagram: A common display for sensitivity analysis is the Tornado Diagram, which graphs the calculated correlation coefficient for each element of the quantitative risk model that can influence the project outcome.

Other Quantitative Techniques: Perform Quantitative Risk Analysis also utilizes:

Representations of Uncertainty (e.g., probability distributions like beta, triangular, or lognormal).

Decision Tree Analysis (to evaluate the Expected Monetary Value - EMV).

Influence Diagrams.

Simulations (typically using Monte Carlo analysis to provide a distribution of possible project durations or costs).

Comparison with other options:

B. Probability and impact matrix: This is a tool used in Perform Qualitative Risk Analysis. It is a descriptive (non-numerical) method used to prioritize risks by mapping their probability and impact into categories like " High, " " Medium, " or " Low. "

C. Risk data quality assessment: This is a technique used in Perform Qualitative Risk Analysis to evaluate the degree to which the data about individual project risks is accurate and reliable.

D. Risk categorization: This is a technique used in Perform Qualitative Risk Analysis to group risks by sources (using a Risk Breakdown Structure), by area of the project affected, or other useful categories to identify the areas of the project most exposed to the effects of uncertainty.