High Quality Content by WIKIPEDIA articles! In statistics and optimization, statistical errors and residuals are two closely related and easily confused measures of the deviation of a sample from its “theoretical value”. The error of a sample is the deviation of the sample from the (unobservable) true function value; while the residual of a sample is the difference between the sample and the estimated function value. The distinction is most important in regression analysis, where it leads to the concept of studentized residuals.

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