PMI-RMP Risk Process Facilitation Practice Question
You are facilitating a risk analysis session for a project with high technical uncertainty. Quantitative analysis results show a wide range of variance. What is the most appropriate action to improve the accuracy of the risk model?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Incorporate sensitivity analysis (Tornado Diagram) to refine input assumptions
Updating the risk model with more precise expert estimates or empirical data is the best way to tighten the variance in quantitative models.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Increase the number of iterations in the Monte Carlo simulation
Why it's wrong here
Increasing iterations reduces sampling error but does not fix inaccurate input assumptions.
- ✓
Incorporate sensitivity analysis (Tornado Diagram) to refine input assumptions
Why this is correct
Tornado diagrams help identify which variables most influence the outcome, allowing for targeted refinement of those specific estimates.
- ✗
Remove the extreme outliers from the risk dataset
Why it's wrong here
Removing data points without justification introduces bias into the quantitative analysis.
- ✗
Change the probability distribution type from Normal to Triangular
Why it's wrong here
Changing the distribution without empirical evidence is arbitrary and may mislead the model.
About these practice questions
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed August 2026 · checked against the official PMI exam blueprint
This PMI-RMP practice question is part of Courseiva's free PMI certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the PMI-RMP exam.