In statistics, rank correlation is the study of relationships between different rankings on the same set of items. It deals with measuring correspondence between two rankings, and assessing the significance of this correspondence.
Two of the more popular rank correlation statistics are
- Spearman's rank correlation coefficient (Spearman's ρ)
- Kendall's tau rank correlation coefficient (Kendall's τ)
A rank correlation coefficient is in the interval [-1,1] where:
- If the agreement between the two rankings is perfect (i.e., the two rankings are the same) the coefficient has value 1.
- If the disagreement between the two rankings is perfect (i.e., one ranking is the reverse of the other) the coefficient has value -1.
- For all other arrangements the value lies between -1 and 1, and increasing values imply increasing agreement between the rankings.
- If the rankings are completely independent, the coefficient has value 0.