PMI-RMP · Question #121
Sensitivity analysis is a technique for systematically changing parameters in a model to determine the effects of such changes and is useful for computer modelers for a range of purposes. Which of the
The correct answer is B. Model development C. Decision making or the development of recommendations for decision makers D. Increased understanding or quantification of the system. Sensitivity analysis serves multiple purposes in project and system modeling, excluding the estimation of average outcomes. The correct purposes are model development, decision making, and increased system understanding.
Question
Sensitivity analysis is a technique for systematically changing parameters in a model to determine the effects of such changes and is useful for computer modelers for a range of purposes. Which of the following purposes does the sensitivity analysis include? Each correct answer represents a complete solution. Choose all that apply.
Options
- AEstimating the average outcome
- BModel development
- CDecision making or the development of recommendations for decision makers
- DIncreased understanding or quantification of the system
How the community answered
(43 responses)- A9% (4)
- B91% (39)
Why each option
Sensitivity analysis serves multiple purposes in project and system modeling, excluding the estimation of average outcomes. The correct purposes are model development, decision making, and increased system understanding.
Estimating the average outcome is a function of expected value analysis or Monte Carlo simulation, not sensitivity analysis, which focuses on the effect of parameter changes rather than producing a single mean result.
Sensitivity analysis is used during model development to identify which input parameters most influence model outputs, helping refine and validate the model structure.
Sensitivity analysis supports decision making by showing how changes in key variables affect outcomes, enabling informed recommendations for stakeholders and decision makers.
Sensitivity analysis increases understanding of a system by quantifying how uncertainty in inputs propagates to uncertainty in outputs, revealing the key drivers of system behavior.
Concept tested: Purposes and applications of sensitivity analysis
Source: https://www.pmi.org/pmbok-guide-standards/foundational/pmbok
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