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Parametric Cost Estimating

Parametric cost estimating uses a statistical relationship between historical data and other variables to calculate a cost estimate for project work.

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Explanation

Parametric estimating uses an algorithm or mathematical model to estimate costs based on historical data and project parameters. For example, if historical data shows that a square foot of construction costs $200, and the project requires 10,000 square feet, the parametric estimate would be $2,000,000.

The accuracy of parametric estimates depends on the sophistication and reliability of the underlying model and the data used. This technique can be applied to an entire project or to parts of a project, and it can be used in conjunction with other estimating methods.

Parametric estimating can produce higher levels of accuracy than analogous estimating depending on the maturity of the model and the data. It is most reliable when the historical data used to develop the model is accurate, the parameters used in the model are readily quantifiable, and the model is scalable.

Key Points

  • Uses statistical relationships and mathematical models
  • Accuracy depends on the quality of the underlying model and data
  • Can be highly accurate when the model is mature and data is reliable
  • Scalable across different project sizes

Exam Tip

Parametric estimating uses a unit rate multiplied by quantity (e.g., cost per line of code multiplied by number of lines). It is more accurate than analogous when the model is sound.

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