estimates

An estimate is an approximate value or judgment of a quantity or outcome, produced when complete information is unavailable. Estimates are used across science, engineering, economics, business, and policy to inform decisions and planning. They are not exact measurements, and they typically include some stated uncertainty derived from data, models, or prior experience.

Point estimates yield a single best guess for a parameter or quantity. Interval estimates provide a range that is believed to contain the true value with a stated level of confidence or probability (for example, a 95% interval).

Estimation methods range from deterministic calculations to probabilistic models. Data sources can include historical measurements, analogies, and expert judgment. Common techniques include regression and other statistical methods, maximum likelihood estimation, Bayesian inference, and Monte Carlo simulation to propagate uncertainty.

Uncertainty is an inherent feature of estimates. Two important concepts are accuracy (closeness to the true value) and precision (width of the estimate’s range). Bias, sample quality, and model misspecification can distort estimates, and sensitivity analysis is used to assess how results change with assumptions.

Applications are widespread. In project management, estimates underpin budgeting and scheduling. In engineering, they determine quantities of materials and expected performance. In software development, effort and size estimates guide staffing and timelines. In economics, forecast estimates inform policy and market expectations.

Estimates are revised as new information becomes available. Clear communication of assumptions and the associated uncertainty is essential for effective decision making.