CAPM Predictive Plan-Based Methodologies Practice Question
A project team is conducting cost estimation for a project that uses a predictive lifecycle. They have historical data from similar projects. Which estimation technique is MOST appropriate?
⚠ Common exam trap
The trap is confusing 'historical data from similar projects' (analogous) with 'historical data and a statistical relationship' (parametric); the presence of a unit rate or formula is the tell for parametric.
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
✓
Analogous estimating
Analogous estimating uses historical data from similar past projects to estimate the current project's cost or duration, which is exactly what the team has available. It is a top-down, expert-judgment-based technique that is fast and inexpensive, making it well suited to predictive lifecycles where scope is relatively stable and comparable projects exist.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Three-point estimating
Why it's wrong here
Three-point estimating uses optimistic, pessimistic, and most likely values for a single activity; it does not exploit the historical data from comparable completed projects described here. It suits uncertain individual tasks where analogous or parametric data is unavailable.
- ✓
Analogous estimating
Why this is correct
Analogous estimating uses historical data from comparable past projects to derive cost figures, which suits a predictive lifecycle with limited detail. It satisfies the stem's constraint of available historical data from similar projects, delivering a quick top-down estimate, though less accurate than bottom-up or parametric methods.
- ✗
Parametric estimating
Why it's wrong here
Parametric estimating applies a statistical relationship between historical data and variables such as units or duration; the stem supplies analogous projects, not a scalable unit rate, so analogous estimating fits. Parametric is tempting because it uses historical data, but it requires a quantifiable cost driver per unit.
- ✗
Bottom-up estimating
Why it's wrong here
Bottom-up estimating aggregates individual work-package estimates, which is laborious and unnecessary when analogous historical data already exists for similar predictive projects. It is tempting because it yields the greatest accuracy when detailed scope is decomposed and no comparable past data is available.
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Last reviewed September 2026 · checked against the official PMI exam blueprint
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