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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“O for a man who is a man, and, as my neighbor says, has a bone in his back which you cannot pass your hand through! Our statistics are at fault: the population has been returned too large. How many men are there to a square thousand miles in this country? Hardly one.”
—Henry David Thoreau (1817–1862)