Just because it is obvious to you doesn’t mean that everybody immediately jumps to it. Me included and I like the statistics classes back then. Could you please point to the wheels?
One example of a good robust estimator for the center is the [truncated mean]https://en.wikipedia.org/wiki/Truncated_mean). To put it simply: throw away the lowest x% and the highest x% of the samples, and take the mean of the rest. If x=0 you get the regular mean, if x=50% then you get the median.
“Please do my literature search for me” is not a reasonable request, though.
Knowing the term of art is very helpful for doing these sorts of searches, though. If one goes to the wikipedia page on summary statistics, one can easily get to the page for descriptive statistics, but neither of them are very good at leading one on to robust statistics, or anything besides the mean or median.
Just because it is obvious to you doesn’t mean that everybody immediately jumps to it. Me included and I like the statistics classes back then. Could you please point to the wheels?
The wheels in this case come from robust statistics.
One example of a good robust estimator for the center is the [truncated mean]https://en.wikipedia.org/wiki/Truncated_mean). To put it simply: throw away the lowest x% and the highest x% of the samples, and take the mean of the rest. If x=0 you get the regular mean, if x=50% then you get the median.
Descriptive statistics, also, probably.
“Please do my literature search for me” is not a reasonable request, though.
Knowing the term of art is very helpful for doing these sorts of searches, though. If one goes to the wikipedia page on summary statistics, one can easily get to the page for descriptive statistics, but neither of them are very good at leading one on to robust statistics, or anything besides the mean or median.
Google for “summary statistics” is sufficient. But more importantly, lit. search isn’t a google/wikipedia type of activity.