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
Famous quotes containing the words errors and/or statistics:
“Truth has not single victories; all things are its organs,—not only dust and stones, but errors and lies.”
—Ralph Waldo Emerson (1803–1882)
“We already have the statistics for the future: the growth percentages of pollution, overpopulation, desertification. The future is already in place.”
—Günther Grass (b. 1927)