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  2. Pearson correlation coefficient - Wikipedia

    en.wikipedia.org/.../Pearson_correlation_coefficient

    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. Correlation coefficient - Wikipedia

    en.wikipedia.org/wiki/Correlation_coefficient

    A correlation coefficient is a numerical measure of some type of linear correlation, meaning a statistical relationship between two variables. [a] The variables may be two columns of a given data set of observations, often called a sample, or two components of a multivariate random variable with a known distribution.

  4. Correlation - Wikipedia

    en.wikipedia.org/wiki/Correlation

    Some correlation statistics, such as the rank correlation coefficient, are also invariant to monotone transformations of the marginal distributions of X and/or Y. Pearson/Spearman correlation coefficients between X and Y are shown when the two variables' ranges are unrestricted, and when the range of X is restricted to the interval (0,1).

  5. Spearman's rank correlation coefficient - Wikipedia

    en.wikipedia.org/wiki/Spearman's_rank_correlation...

    In statistics, Spearman's rank correlation coefficient or Spearman's ρ, named after Charles Spearman [1] and often denoted by the Greek letter (rho) or as , is a nonparametric measure of rank correlation (statistical dependence between the rankings of two variables).

  6. Covariance and correlation - Wikipedia

    en.wikipedia.org/wiki/Covariance_and_correlation

    Notably, correlation is dimensionless while covariance is in units obtained by multiplying the units of the two variables. If Y always takes on the same values as X , we have the covariance of a variable with itself (i.e. σ X X {\displaystyle \sigma _{XX}} ), which is called the variance and is more commonly denoted as σ X 2 , {\displaystyle ...

  7. Phi coefficient - Wikipedia

    en.wikipedia.org/wiki/Phi_coefficient

    In statistics, the phi coefficient (or mean square contingency coefficient and denoted by φ or r φ) is a measure of association for two binary variables.. In machine learning, it is known as the Matthews correlation coefficient (MCC) and used as a measure of the quality of binary (two-class) classifications, introduced by biochemist Brian W. Matthews in 1975.

  8. Notation in probability and statistics - Wikipedia

    en.wikipedia.org/wiki/Notation_in_probability...

    the sample correlation coefficient, the sample cumulants . Some commonly used symbols for population parameters are given below: the population mean , the population variance , the population standard deviation ,

  9. Cramér's V - Wikipedia

    en.wikipedia.org/wiki/Cramér's_V

    φ c 2 is the mean square canonical correlation between the variables. [ citation needed ] In the case of a 2 × 2 contingency table Cramér's V is equal to the absolute value of Phi coefficient .