Other Uses of The Word "error" in Statistics
The use of the term "error" as discussed in the sections above is in the sense of a deviation of a value from a hypothetical unobserved value. At least two other uses also occur in statistics, both referring to observable prediction errors:
Mean square error or mean squared error (abbreviated MSE) and root mean square error (RMSE) refer to the amount by which the values predicted by an estimator differ from the quantities being estimated (typically outside the sample from which the model was estimated).
Sum of squared errors, typically abbreviated SSE or SSe, refers to the residual sum of squares (the sum of squared residuals) of a regression; this is the sum of the squares of the deviations of the actual values from the predicted values, within the sample used for estimation. Likewise, the sum of absolute errors (SAE) refers to the sum of the absolute values of the residuals, which is minimized in the least absolute deviations approach to regression.
Read more about this topic: Errors And Residuals In Statistics
Famous quotes containing the words statistics, word and/or error:
“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)
“I curse all negative purism that tells me not to use a word from another language that either expresses something that my own language cannot or does that in a more delicate manner.”
—Johann Wolfgang Von Goethe (17491832)
“Error is a supposition that pleasure and pain, that intelligence, substance, life, are existent in matter. Error is neither Mind nor one of Minds faculties. Error is the contradiction of Truth. Error is a belief without understanding. Error is unreal because untrue. It is that which seemeth to be and is not. If error were true, its truth would be error, and we should have a self-evident absurditynamely, erroneous truth. Thus we should continue to lose the standard of Truth.”
—Mary Baker Eddy (18211910)