Timeline for Visual inspection versus Shapiro-Wilk test for normality
Current License: CC BY-SA 4.0
9 events
| when toggle format | what | by | license | comment | |
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| Oct 6, 2021 at 6:04 | history | bumped | CommunityBot | This question has answers that may be good or bad; the system has marked it active so that they can be reviewed. | |
| Jun 6, 2021 at 7:01 | history | bumped | CommunityBot | This question has answers that may be good or bad; the system has marked it active so that they can be reviewed. | |
| May 5, 2021 at 1:39 | answer | added | kjetil b halvorsen♦ | timeline score: 2 | |
| May 5, 2021 at 1:34 | history | edited | kjetil b halvorsen♦ |
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| Jan 29, 2019 at 7:29 | comment | added | Glen_b | Do not interpret p-value as effect size. "- in other words not very normal". With large samples you may have very low p-values with small effect sizes. | |
| Jan 28, 2019 at 22:49 | comment | added | whuber♦ | @gung I would have guessed approximately $-1/2 / \Phi^{-1}(-3.6)\approx 3150$ observations because the most extreme "norm quantiles" are near $\pm 3.6.$ | |
| Jan 28, 2019 at 20:58 | comment | added | adrianmcmenamin | The data is about times a benchmark takes to complete a task in a complex computing system. In this case I have 3085 observations but I am seeking a general answer if possible - I am interested in the top end because I want to apply statistical methods to estimate worst case execution times. | |
| Jan 28, 2019 at 20:55 | comment | added | gung - Reinstate Monica | How many data do you have? (At least 260, I'm guessing.) What are these data? Why does there seem to be a floor? What is it that you really want such that you only care about the top end? | |
| Jan 28, 2019 at 20:51 | history | asked | adrianmcmenamin | CC BY-SA 4.0 |