Timeline for If two traits have known correlation, can you predict probability they'll "align" for a random pair?
Current License: CC BY-SA 3.0
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| Mar 9, 2016 at 2:17 | history | edited | Glen_b | CC BY-SA 3.0 |
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| Mar 8, 2016 at 23:44 | history | edited | Glen_b | CC BY-SA 3.0 |
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| Mar 8, 2016 at 23:37 | history | edited | Glen_b | CC BY-SA 3.0 |
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| Mar 8, 2016 at 23:25 | comment | added | Glen_b | Indeed that's an excellent question to ponder -- and one might well ask a similar question in relation to a number of other nonparametric quantities of similar interpretability and simplicity. [At least the Kendall correlation is widely used in work with copulas, both the theory and practice.] | |
| Mar 8, 2016 at 23:22 | comment | added | Hypnosifl | I'm approving RobertF's answer since it came first and addressed most of what I was asking, but I appreciate this additional information. My layman's impression is that most of the empirical statistical studies I've seen in fields like medicine/psychology/sociology only use Pearson's r or r^2 to describe correlations--if that's true I wonder why Kendall's measure isn't reported more often alongside it, it would seem to have some usefulness in interpreting the results (especially when summarizing for a non-specialist audience, since the idea of picking a random pair is intuitive). | |
| Mar 8, 2016 at 23:22 | history | edited | Glen_b | CC BY-SA 3.0 |
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| Mar 8, 2016 at 23:11 | history | edited | Glen_b | CC BY-SA 3.0 |
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| Mar 8, 2016 at 23:06 | history | edited | Glen_b | CC BY-SA 3.0 |
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| Mar 8, 2016 at 22:39 | history | answered | Glen_b | CC BY-SA 3.0 |