Which estimating method augments bottom-up or top-down estimates using historical data?

The correct choice is parametric model estimating. This method involves using statistical relationships between historical data and other variables to create estimates for project costs, durations, and resources. It enhances both bottom-up and top-down estimates by applying specific data points from previous projects to inform the current estimate. For instance, if historical data shows that a certain type of project typically costs $100,000 and takes six months to complete, these figures can guide the estimation for similar upcoming projects, adding a layer of validation and accuracy.

In contrast, top-down estimating relies more heavily on overall project parameters and may lack the granularity that parametric approaches offer since it starts with a total budget or timeline and allocates resources. Analogous estimating, while also based on historical data, does not utilize statistical relationships and may offer less precise results than the parametric method. Expert judgment involves relying on the experience and intuition of knowledgeable individuals but does not systematically incorporate historical data in the same structured way that parametric models do. Thus, parametric model estimating is particularly effective as it utilizes the strength of historical data directly in a statistical framework to refine estimates beyond what other methods might achieve alone.