Timeline for Correlations between continuous and categorical (nominal) variables
Current License: CC BY-SA 3.0
18 events
| when toggle format | what | by | license | comment | |
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| Jul 1 at 3:54 | answer | added | Talal Manshoor | timeline score: 0 | |
| Jun 13 at 13:24 | history | edited | whuber♦ |
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| Jun 3, 2021 at 0:58 | answer | added | SriK | timeline score: 0 | |
| Oct 19, 2018 at 10:55 | history | edited | kjetil b halvorsen♦ |
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| Aug 16, 2018 at 0:00 | answer | added | aerijman | timeline score: 1 | |
| Dec 25, 2015 at 20:59 | comment | added | ttnphns | Correlation between nominal and interval or ordinal variable stats.stackexchange.com/q/73065/3277 | |
| Dec 25, 2015 at 19:09 | answer | added | Jon | timeline score: 12 | |
| Jun 11, 2015 at 23:39 | answer | added | brca1 | timeline score: 1 | |
| S Jun 10, 2014 at 12:48 | history | suggested | CommunityBot | CC BY-SA 3.0 |
Grammar fix and rephrasal
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| Jun 10, 2014 at 12:45 | review | Suggested edits | |||
| S Jun 10, 2014 at 12:48 | |||||
| Jun 10, 2014 at 11:41 | vote | accept | Md. Ferdous Wahid | ||
| Jun 10, 2014 at 11:19 | answer | added | kjetil b halvorsen♦ | timeline score: 44 | |
| Jun 10, 2014 at 9:03 | comment | added | Md. Ferdous Wahid | Yes, my question is similar to that. However, I got a feedback where reviewer indicated that Spearman's $\rho$ is not appropriate. My sample size is 31. According to the answer (the link provided), non-normal wouldn't be an issue and any correlation method can be used (Spearman/Pearson/Point-Biserial) for the large dataset. Would it be true for the small dataset too? By the way, gender is not an artificially created dichotomous nominal scale. The above link should use biserial correlation coefficient. | |
| Jun 10, 2014 at 8:41 | comment | added | kjetil b halvorsen♦ | Seems like a duplicate of stats.stackexchange.com/questions/25229/… Can you tell us if the answers to that one helps you? | |
| Jun 10, 2014 at 8:37 | comment | added | Md. Ferdous Wahid | Thanks kjetil, I would like to compare the association between gender and other continuous variables. Simply to know, which continuous variables are moderately/strongly correlated and which variables are not. | |
| Jun 10, 2014 at 8:32 | history | edited | Md. Ferdous Wahid | CC BY-SA 3.0 |
added 60 characters in body
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| Jun 10, 2014 at 8:29 | comment | added | kjetil b halvorsen♦ | Normally, one cannot advice only on the basis of the format of the data! What do the data represent, and what do you want to achieve with your analysis? | |
| Jun 10, 2014 at 8:13 | history | asked | Md. Ferdous Wahid | CC BY-SA 3.0 |