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Quantitative Risk Analysis Flashcards

7 cards from real PMI-RMP practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.

Read the first 7 Quantitative Risk Analysis flashcards as text
  1. In a Monte Carlo simulation of project cost, what does the P80 value on the cumulative S-curve represent?

    Answer: An 80% chance the actual cost will be at or below that value

    P80 means there is an 80% probability the outcome will be at or below that cost value.

  2. A risk has a 30% probability and would cost $50,000 if it occurs. What is its expected monetary value (EMV)?

    Answer: $15,000

    EMV equals probability times impact, so 0.30 × $50,000 = $15,000.

  3. Which distribution is most commonly used in three-point estimating with optimistic, most likely, and pessimistic values?

    Answer: Triangular or PERT (beta) distribution

    Three-point estimates feed triangular or PERT/beta distributions in quantitative analysis.

  4. In a decision tree, what does the EMV at a decision node typically guide the project manager to choose?

    Answer: The branch with the most favorable expected monetary value

    Decision-tree analysis selects the path with the best expected monetary value.

  5. A tornado diagram in quantitative risk analysis is primarily used to display what?

    Answer: The relative sensitivity of an outcome to individual risk variables

    Tornado diagrams rank variables by how strongly they influence the outcome, showing sensitivity.

  6. What is the main reason a project uses Monte Carlo simulation instead of a single deterministic estimate?

    Answer: It models combined uncertainty to produce a range of probable outcomes

    Monte Carlo captures combined uncertainty, yielding a probability distribution rather than one number.

  7. When running a schedule risk simulation, which network paths are most likely to become critical under uncertainty?

    Answer: Near-critical paths with high duration variability

    Near-critical paths with high variability can overtake the original critical path, revealing criticality risk.

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