Errors And Residuals In Statistics
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.
Read more about Errors And Residuals In Statistics: Introduction, Regressions, Other Uses of The Word "error" in Statistics
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—Ralph Waldo Emerson (1803–1882)
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—E.E. (Edward Estlin)