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, 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)
“Their errors have been weighed and found to have been dust in the balance; if their sins were as scarlet, they are now white as snow: they have been washed in the blood of the mediator and the redeemer, Time.”
—Percy Bysshe Shelley (1792–1822)
“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)