4 ms·
For a one-sided, unbounded distribution when you still want to observe changes without being susceptible to outliers. If you're monitoring response timings on
by ivanbakel 3y ago
For a one-sided, unbounded distribution when you still want to observe changes without being susceptible to outliers.
If you're monitoring response timings on a server, for example, the median might be very close to 0, and it won't shift unless a majority of the distribution slows down. If you take a winsorised mean, you can trim useless long response times that mess with the mean, but still see if e.g. 1/3 of your responses are suddenly slower than normal.
- timeagain 3y agoBut wouldn’t the trimmed mean mentioned in the article do this without “windsoriszing”?
- myhf 3y agoThe trimmed mean discards outliers, so it can measure "what is the typical value for non-outliers?". The windsorized mean reduces the weight of outliers, so it can measure "how many outliers are there?" instead of "how extreme are the outliers?"