Timeline for How to choose between Pearson and Spearman correlation?
Current License: CC BY-SA 4.0
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| Jan 30, 2021 at 1:07 | history | edited | Nick Cox | CC BY-SA 4.0 |
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| Mar 10, 2011 at 10:37 | comment | added | richiemorrisroe | @ steffen: you are correct about the heresy, but if the two procedures give the same results then its a matter of taste which to use, but if they dont then checking the asumptions and where they fail can often give useful insight into the data. Personally, i use spearman wherever possible, but this is not common practice in my field. | |
| Mar 9, 2011 at 14:26 | comment | added | steffen | @Glen: In this case I cannot. But when I compare the quality of different models, I generally prefer to check the assumption (e.g. approximately normally distributed) before performing the test to reduce the tendency to relax assumptions in favor of certain test outcomes. Call it prevention of a mind trick. I guess it is just me ;). | |
| Mar 9, 2011 at 13:27 | comment | added | Glen | @steffen I think it's fine. One assumption of regression is that the residuals are normally distributed. How would you check that before running the regression? | |
| Mar 9, 2011 at 12:11 | comment | added | steffen | as a machine learner I am certainly not a saint regarding statistical correctness, but checking the assumptions AFTER performing the test seems like heresy to me. | |
| Mar 9, 2011 at 11:54 | history | answered | richiemorrisroe | CC BY-SA 2.5 |