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I need some reading suggestions on Kendall's Tau at undergraduate level . I am not able to find some good material on the above topic . Please help me out .

EDIT: To be more specific ,I want some motivation for the tau a,b,c formulae with some applications . My intended meaning for 'undergraduate' I am an undergrad in statistics currently in freshman year .

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  • $\begingroup$ Your question is not sufficiently clear. Can you explain what you seek that is not covered by the references and further reading at the bottom of the article on the WIkipedia page for this correlation measure? (i.e. what would make a reference 'good' for your purposes?). Further "undergraduate" spans a wide variety of knowledge and ability; much of the reference list would be within the grasp of an undergraduate in statistics late in their studies, but some of it would be hard going for (say) an undergraduate in psychology early in theirs. $\endgroup$
    – Glen_b
    Oct 22, 2018 at 2:52
  • $\begingroup$ @Glen_b , I want some motivation for the tau a,b,c formulae with some applications . I am an undergrad in statistics currently in freshman year . $\endgroup$
    – John
    Oct 22, 2018 at 3:10
  • $\begingroup$ That may help a bit. Could you edit that into your question please? $\endgroup$
    – Glen_b
    Oct 22, 2018 at 3:15

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Kendall’s Tau is a non-parametric measure of relationships between columns of ranked data. The Tau correlation coefficient returns a value of 0 to 1, where:

0 is no relationship, 1 is a perfect relationship. A quirk of this test is that it can also produce negative values (i.e. from -1 to 0). Unlike a linear graph, a negative relationship doesn’t mean much with ranked columns (other than you perhaps switched the columns around), so just remove the negative sign when you’re interpreting Tau.

Several version’s of Tau exist.

Tau-A and Tau-B are usually used for square tables (with equal columns and rows). Tau-B will adjust for tied ranks. Tau-C is usually used for rectangular tables. For square tables, Tau-B and Tau-C are essentially the same.

Reference from links:
1. http://www.vias.org/tmdatanaleng/ee_kendall_rank_correlation.html
2. https://www.statisticshowto.datasciencecentral.com/kendalls-tau/

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