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Parametric Estimating

Parametric estimating uses a statistical relationship between historical data and other variables to calculate an estimate for activity parameters such as cost, budget, and duration.

Explanation

Parametric estimating applies mathematical models to historical data to produce estimates. It uses a known unit rate or productivity factor multiplied by the quantity of work to calculate the total duration or cost. For example, if historical data shows that a team can install 50 meters of cable per day, and the project requires 500 meters, the parametric estimate for that activity would be 10 days.

The accuracy of parametric estimating depends heavily on the quality of the underlying data model and the scalability of the parameters. If the historical data is based on reliable measurements and the relationship between the variable and the result is consistent, parametric estimates can be highly accurate. However, if the data model does not scale well (for example, productivity rates that change at higher volumes) or the data is unreliable, the estimates will be less accurate.

Parametric estimating can be applied to an entire project or to individual activities. It is often more accurate than analogous estimating because it relies on quantified relationships rather than subjective judgment. It can also be combined with other techniques. For instance, a parametric estimate might be used as a starting point and then refined with expert judgment or three-point estimating.

Key Points

  • Uses statistical relationships between historical data and variables
  • Applies unit rates or productivity factors to quantities of work
  • More accurate than analogous estimating when data models are reliable
  • Can be applied at the project or activity level

Exam Tip

Parametric estimating uses math (unit rate x quantity). Example: 200 lines of code per day x 1,000 lines = 5 days. Know how to calculate this on the exam.

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