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  2. Uncertainty coefficient - Wikipedia

    en.wikipedia.org/wiki/Uncertainty_coefficient

    In statistics, the uncertainty coefficient, also called proficiency, entropy coefficient or Theil's U, is a measure of nominal association. It was first introduced by Henri Theil [citation needed] and is based on the concept of information entropy.

  3. DFFITS - Wikipedia

    en.wikipedia.org/wiki/DFFITS

    In statistics, DFFIT and DFFITS ("difference in fit(s)") are diagnostics meant to show how influential a point is in a linear regression, first proposed in 1980. [ 1 ] DFFIT is the change in the predicted value for a point, obtained when that point is left out of the regression:

  4. Sheppard's correction - Wikipedia

    en.wikipedia.org/wiki/Sheppard's_correction

    In statistics, Sheppard's corrections are approximate corrections to estimates of moments computed from binned data. The concept is named after William Fleetwood Sheppard . Let m k {\displaystyle m_{k}} be the measured k th moment, μ ^ k {\displaystyle {\hat {\mu }}_{k}} the corresponding corrected moment, and c {\displaystyle c} the breadth ...

  5. Fieller's theorem - Wikipedia

    en.wikipedia.org/wiki/Fieller's_theorem

    Fieller, EC (1944). "A fundamental formula in the statistics of biological assay, and some applications". Quarterly Journal of Pharmacy and Pharmacology. 17: 117– 123. Motulsky, Harvey (1995) Intuitive Biostatistics. Oxford University Press. ISBN 0-19-508607-4; Senn, Steven (2007) Statistical Issues in Drug Development. Second Edition. Wiley.

  6. Completeness (statistics) - Wikipedia

    en.wikipedia.org/wiki/Completeness_(statistics)

    In statistics, completeness is a property of a statistic computed on a sample dataset in relation to a parametric model of the dataset. It is opposed to the concept of an ancillary statistic . While an ancillary statistic contains no information about the model parameters, a complete statistic contains only information about the parameters, and ...

  7. Rule of three (statistics) - Wikipedia

    en.wikipedia.org/wiki/Rule_of_three_(statistics)

    The rule can then be derived [2] either from the Poisson approximation to the binomial distribution, or from the formula (1−p) n for the probability of zero events in the binomial distribution. In the latter case, the edge of the confidence interval is given by Pr(X = 0) = 0.05 and hence (1−p) n = .05 so n ln(1–p) = ln .05 ≈ −2

  8. Johnson's SU-distribution - Wikipedia

    en.wikipedia.org/wiki/Johnson's_SU-distribution

    This article needs attention from an expert in statistics. The specific problem is: completion to reasonable standard for probability distributions. WikiProject Statistics may be able to help recruit an expert.

  9. Savitzky–Golay filter - Wikipedia

    en.wikipedia.org/wiki/Savitzky–Golay_filter

    For two passes of the same filter this is equivalent to one pass of a filter obtained by convolution of the original filter with itself. [29] For example, 2 passes of the filter with coefficients (1/3, 1/3, 1/3) is equivalent to 1 pass of the filter with coefficients (1/9, 2/9, 3/9, 2/9, 1/9).