Which of the following is an example of a technique used in quantitative risk analysis?

Question

Options

• ASensitivity analysis
• BProbability and impact matrix
• CRisk data quality assessment
• DRisk categorization

• A
  74% (23)
• B
  3% (1)
• C
  13% (4)
• D
  10% (3)

Explanation

Sensitivity analysis belongs to quantitative risk analysis because it uses numerical data - typically a tornado diagram - to measure how changes in individual risk variables affect overall project outcomes, producing a ranked, measurable result.

Why the distractors are wrong:

• B (Probability and impact matrix) is a qualitative tool - it ranks risks using descriptive scales (high/medium/low), not numbers.
• C (Risk data quality assessment) is also qualitative - it evaluates how reliable the risk information is before analyzing it, with no numerical computation.
• D (Risk categorization) is qualitative - it groups risks (e.g., technical, external) to organize them, not to quantify them.

Memory tip: Think "Quant = Numbers." Quantitative techniques produce numeric outputs - dollar amounts, probabilities as decimals, schedule impact in days. The classic quantitative tools are sensitivity analysis, Monte Carlo simulation, Expected Monetary Value (EMV), and decision tree analysis. If a technique uses words like "high/medium/low" or just organizes/describes risks, it's qualitative.

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