Timeline for t-test when the data population is not normally distributed
Current License: CC BY-SA 4.0
7 events
| when toggle format | what | by | license | comment | |
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| Dec 31, 2022 at 19:24 | history | edited | kjetil b halvorsen♦ | CC BY-SA 4.0 |
added 33 characters in body
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| May 24, 2020 at 19:51 | vote | accept | Angadishop | ||
| May 14, 2020 at 15:31 | comment | added | Stephan Kolassa | Nonparametric tests have their place if $n$ is small. For medium-sized $n$, one can bootstrap the test statistic to get a feeling for whether asymptotics have already kicked in. I used to hand-code permutation alternatives to parametric tests in quite complicated situations precisely because I was afraid the $n$ was not yet large enough, and found to my dismay that p values were very close to the ones from the parametric test. In the end, it really comes down to experience. | |
| May 14, 2020 at 15:04 | comment | added | Angadishop | Thank you, this made a lot of things clear but, this brings up another question. So according to CLT, the mean of the sample or the test statistic will be asymptotically normal at some 'n' for any underlying distribution. Then when do we move to non-parametric tests like wilcoxon and how do we check for the asymptotic normality of test statistic? In real life we will have only one value for test statistic. | |
| May 14, 2020 at 6:52 | comment | added | Stephan Kolassa | @BruceET: Thank you! I would also be interested in the reason for the downvote. | |
| May 14, 2020 at 6:44 | comment | added | BruceET | Down-vote is a puzzlement. So (+1) now. Similar recent Q&A. Permutation test is nice idea. | |
| May 14, 2020 at 6:11 | history | answered | Stephan Kolassa | CC BY-SA 4.0 |