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Multivariate correlation analysis plays an important role in various fieldssuch as statistics and big data analytics. In this paper, it is presented a newnon-parametric measure of rank correlation between more than two variables fromthe multivariate generalization of the Kendall's Tau coefficient (Tau-N). Thismultivariate correlation analysis not only evaluates the inter-relatedness ofmultiple variables, but also determine the specific tendency of the tested dataset. Additionally, it is discussed how the discordant concept would have somelimitations when applied to more than two variables, for which reason thismethodology has been developed based on the new concept paired orthants. Inorder to test the proposed methodology, different N-tuple sets (from two to sixvariables) have been evaluated.

Multivariate generalization of Kendall's Tau (Tau-N) using paired orthants