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  2. 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]

  3. Errors and residuals - Wikipedia

    en.wikipedia.org/wiki/Errors_and_residuals

    In regression analysis, the distinction between errors and residuals is subtle and important, and leads to the concept of studentized residuals. Given an unobservable function that relates the independent variable to the dependent variable – say, a line – the deviations of the dependent variable observations from this function are the ...

  4. Studentization - Wikipedia

    en.wikipedia.org/wiki/Studentization

    A simple example is the process of dividing a sample mean by the sample standard deviation when data arise from a location-scale family. The consequence of "Studentization" is that the complication of treating the probability distribution of the mean, which depends on both the location and scale parameters, has been reduced to considering a ...

  5. Studentized range distribution - Wikipedia

    en.wikipedia.org/wiki/Studentized_range_distribution

    The studentized range distribution function arises from re-scaling the sample range R by the sample standard deviation s, since the studentized range is customarily tabulated in units of standard deviations, with the variable q = R ⁄ s. The derivation begins with a perfectly general form of the distribution function of the sample range, which ...

  6. Studentized range - Wikipedia

    en.wikipedia.org/wiki/Studentized_range

    Generally, the term studentized means that the variable's scale was adjusted by dividing by an estimate of a population standard deviation (see also studentized residual). The fact that the standard deviation is a sample standard deviation rather than the population standard deviation, and thus something that differs from one random sample to ...

  7. 68–95–99.7 rule - Wikipedia

    en.wikipedia.org/wiki/68–95–99.7_rule

    Given a sample set, one can compute the studentized residuals and compare these to the expected frequency: points that fall more than 3 standard deviations from the norm are likely outliers (unless the sample size is significantly large, by which point one expects a sample this extreme), and if there are many points more than 3 standard ...

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  9. DFFITS - Wikipedia

    en.wikipedia.org/wiki/DFFITS

    DFFITS is the Studentized DFFIT, where Studentization is achieved by dividing by the estimated standard deviation of ... of the externally Studentized residual ...