Steven D'Aprano added the comment: On Tue, Dec 13, 2016 at 10:17:21AM +0000, Srikanth Anantharam wrote: > > Srikanth Anantharam added the comment: > > @steven: > > data = [1, 2, 3, 4, 4, 4, 5, 6, 7, 7, 8, 8, 8, 8, 8, 8, 8, 9, 9] > is clearly unimodal with mode 8 > > data would have been bimodal if 4 repeated exactly the same (7) number of > times as 8, like this: > data = [1, 2, 3, 4, 4, 4, 4, 4, 4, 4, 5, 6, 7, 7, 8, 8, 8, 8, 8, 8, 8, 9, 9]
Bimodal distributions do not require both modes to be exactly the same height. And certainly when you have a sample from a bimodal distribution, you should not expect exactly the same frequency for the two modes. Just from random sampling error you will expect one or the other to have a larger frequency. You shouldn't take my example too literally. With such a small sample of discrete values, it becomes a (hard) matter of personal judgement. The point I was attempting to make was that identifying sample modes outside of the simplest unimodal case is tricky and requires much thought. ---------- _______________________________________ Python tracker <rep...@bugs.python.org> <http://bugs.python.org/issue28956> _______________________________________ _______________________________________________ Python-bugs-list mailing list Unsubscribe: https://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
