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  2. Errors and residuals - Wikipedia

    en.wikipedia.org/wiki/Errors_and_residuals

    Thus to compare residuals at different inputs, one needs to adjust the residuals by the expected variability of residuals, which is called studentizing. This is particularly important in the case of detecting outliers, where the case in question is somehow different from the others in a dataset. For example, a large residual may be expected in ...

  3. Observational error - Wikipedia

    en.wikipedia.org/wiki/Observational_error

    When either randomness or uncertainty modeled by probability theory is attributed to such errors, they are "errors" in the sense in which that term is used in statistics; see errors and residuals in statistics. Every time a measurement is repeated, slightly different results are obtained.

  4. Root mean square deviation - Wikipedia

    en.wikipedia.org/wiki/Root_mean_square_deviation

    These deviations are called residuals when the calculations are performed over the data sample that was used for estimation (and are therefore always in reference to an estimate) and are called errors (or prediction errors) when computed out-of-sample (aka on the full set, referencing a true value rather than an estimate). The RMSD serves to ...

  5. Regression validation - Wikipedia

    en.wikipedia.org/wiki/Regression_validation

    non-constant variation across the data: scatter plots of residuals versus predictors; for data collected over time, also plots of residuals against time; drift in the errors (data collected over time): run charts of the response and errors versus time; independence of errors: lag plot; normality of errors: histogram and normal probability plot

  6. Error correction model - Wikipedia

    en.wikipedia.org/wiki/Error_correction_model

    ECMs are a theoretically-driven approach useful for estimating both short-term and long-term effects of one time series on another. The term error-correction relates to the fact that last-period's deviation from a long-run equilibrium, the error, influences its short-run dynamics. Thus ECMs directly estimate the speed at which a dependent ...

  7. Studentized residual - Wikipedia

    en.wikipedia.org/wiki/Studentized_residual

    On the other hand, the internally studentized residuals are in the range , where ν = n − m is the number of residual degrees of freedom. If t i represents the internally studentized residual, and again assuming that the errors are independent identically distributed Gaussian variables, then: [2]

  8. Error bar - Wikipedia

    en.wikipedia.org/wiki/Error_bar

    This statistics -related article is a stub. You can help Wikipedia by expanding it.

  9. Category:Errors and residuals - Wikipedia

    en.wikipedia.org/wiki/Category:Errors_and_residuals

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