As of Version 9.0, KendallRankCorrelation has been renamed to KendallTau and is part of the built-in Wolfram Language kernel.

gives Kendall's rank correlation coefficient for the real-valued vectors xlist and ylist.


  • To use KendallRankCorrelation, you first need to load the Multivariate Statistics Package using Needs["MultivariateStatistics`"].
  • Kendall's rank correlation coefficient is a measure of association based on the relative order of consecutive elements in the two lists.
  • Kendall's rank correlation coefficient between and is given by , where is the number of concordant pairs of observations, is the number of discordant pairs, is the number of ties involving only the variable, and is the number of ties involving only the variable.
  • A concordant pair of observations and is one such that both and or both and . A discordant pair of observations is one such that and or and .
  • The arguments xlist and ylist can be any realvalued vectors of equal length.

ExamplesExamplesopen allclose all

Basic Examples  (1)Basic Examples  (1)

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Kendall's rank correlation for two vectors:

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