Propagation of uncertainty, also known as uncertainty propagation or error propagation, refers to the process of assessing how uncertainties in measurements or input variables affect the uncertainty of a derived quantity. When calculating a result based on multiple measured or estimated quantities, each of these inputs may have a certain degree of uncertainty. Understanding how these uncertainties combine is crucial in fields such as experimental physics, engineering, and statistics. ### Key Concepts 1.
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Propagation of uncertainty estimates how measurement errors in inputs affect a calculated result. For small input errors with covariance matrix , linearizing a differentiable function gives the displayed approximation for its variance. For independent errors in a product , the squared relative standard deviations add. Correlated errors need the covariance terms; systematic offsets require separate assessment.