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  2. Pearson correlation coefficient - Wikipedia

    en.wikipedia.org/wiki/Pearson_correlation...

    Pearson's correlation coefficient is the covariance of the two variables divided by the product of their standard deviations. The form of the definition involves a "product moment", that is, the mean (the first moment about the origin) of the product of the mean-adjusted random variables; hence the modifier product-moment in the name.

  3. Taylor diagram - Wikipedia

    en.wikipedia.org/wiki/Taylor_diagram

    Model A, however, has a slightly higher correlation with observations and has the same standard deviation as the observed, whereas model C has too little spatial variability (with a standard deviation of 2.3 mm/day compared to the observed value of 2.9 mm/day).

  4. Correlation - Wikipedia

    en.wikipedia.org/wiki/Correlation

    The correlation coefficient is +1 in the case of a perfect direct (increasing) linear relationship (correlation), −1 in the case of a perfect inverse (decreasing) linear relationship (anti-correlation), [5] and some value in the open interval (,) in all other cases, indicating the degree of linear dependence between the variables. As it ...

  5. Uncorrelatedness (probability theory) - Wikipedia

    en.wikipedia.org/wiki/Uncorrelatedness...

    Uncorrelated random variables have a Pearson correlation coefficient, when it exists, of zero, except in the trivial case when either variable has zero variance (is a constant). In this case the correlation is undefined.

  6. Correlation function (statistical mechanics) - Wikipedia

    en.wikipedia.org/wiki/Correlation_function...

    One common correlation function is the radial distribution function which is seen often in statistical mechanics and fluid mechanics. The correlation function can be calculated in exactly solvable models (one-dimensional Bose gas, spin chains, Hubbard model) by means of Quantum inverse scattering method and Bethe ansatz. In an isotropic XY ...

  7. Biweight midcorrelation - Wikipedia

    en.wikipedia.org/wiki/Biweight_midcorrelation

    Biweight midcorrelation has been shown to be more robust in evaluating similarity in gene expression networks, [2] and is often used for weighted correlation network analysis. Implementations [ edit ]

  8. Goodman and Kruskal's gamma - Wikipedia

    en.wikipedia.org/wiki/Goodman_and_Kruskal's_gamma

    In statistics, Goodman and Kruskal's gamma is a measure of rank correlation, i.e., the similarity of the orderings of the data when ranked by each of the quantities.It measures the strength of association of the cross tabulated data when both variables are measured at the ordinal level.

  9. Regression dilution - Wikipedia

    en.wikipedia.org/wiki/Regression_dilution

    That is, the disattenuated correlation estimate is obtained by dividing the correlation between the estimates by the geometric mean of the separation indices of the two sets of estimates. Expressed in terms of classical test theory, the correlation is divided by the geometric mean of the reliability coefficients of two tests.