Timeline for Spearman's rank correlation coefficient over population
Current License: CC BY-SA 3.0
5 events
| when toggle format | what | by | license | comment | |
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| Apr 20, 2014 at 8:25 | comment | added | Glen_b | If the value of the Spearman correlation is meaningful for you, then certainly calculate it. (If you're just after some general measure of monotonic association, you might like to consider the Kendall correlation which might be more intuitive in interpretation). | |
| Apr 20, 2014 at 7:45 | comment | added | user2314405 | thanks for answering, in my case I'm not interested in knowing the p-value coming from the Spearman's rank correlation, but I need just a number to measure/quantify the correlation. Basically, i'm doing this in R, I'm using the function 'cor' that returns just the correlation value, instead of using 'cor.test' that returns the correlation value plus the corresponding p-value. My only concern is whether this is correct or I should just plot the two variables | |
| Apr 20, 2014 at 0:12 | comment | added | Glen_b | You can measure something over a population. However, if that's really the population to which you want your inference to apply then there's no need to test it. It is what it is. | |
| Apr 19, 2014 at 20:45 | answer | added | John Jiang | timeline score: 1 | |
| Apr 19, 2014 at 15:55 | history | asked | user2314405 | CC BY-SA 3.0 |