# Errors and residuals

## Statistics concept / From Wikipedia, the free encyclopedia

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In statistics and optimization, **errors** and **residuals** are two closely related and easily confused measures of the deviation of an observed value of an element of a statistical sample from its "true value" (not necessarily observable). The **error** of an observation is the deviation of the observed value from the true value of a quantity of interest (for example, a population mean). The **residual** is the difference between the observed value and the *estimated* value of the quantity of interest (for example, a sample mean). The distinction is most important in regression analysis, where the concepts are sometimes called the **regression errors** and **regression residuals** and where they lead to the concept of studentized residuals.
In econometrics, "errors" are also called **disturbances**.^{[1]}^{[2]}^{[3]}

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