Timeline for "Ice skater" / "figure skating" / "ISU" method of discarding outliers
Current License: CC BY-SA 4.0
8 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Sep 11, 2019 at 11:44 | comment | added | Peter Flom | Why do you need a method of excluding outliers? Perhaps you really do, but probably not. And this method does not exclude outliers. It is the trimmed mean. That automatically excludes a certain proportion of values, regardless of whether they are outliers or not. In figure skating, they are almost never outliers. | |
| Sep 10, 2019 at 14:10 | review | Close votes | |||
| Sep 11, 2019 at 11:41 | |||||
| Sep 10, 2019 at 13:21 | answer | added | Hamish Todd | timeline score: 1 | |
| Sep 10, 2019 at 12:52 | comment | added | whuber♦ | This sounds more like a resistant estimator of a mean than "ruling out outliers." Could you elaborate on how you intend to use or interpret the result? | |
| Sep 10, 2019 at 11:55 | comment | added | mkt | Discarding data requires a good reason. Just because a point is different from the rest does NOT make it invalid. | |
| Sep 10, 2019 at 11:15 | comment | added | user2974951 | Looks similar to a trimmed mean. I would not call this a "good" option, you are throwing away possibly good information. | |
| Sep 10, 2019 at 11:15 | review | First posts | |||
| Sep 10, 2019 at 13:50 | |||||
| Sep 10, 2019 at 11:10 | history | asked | Hamish Todd | CC BY-SA 4.0 |