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From: "Joseph L. Casale" <jcasale@activenetwerx.com>
To: =?windows-1256?Q?Python_=FD=5Bpython-list=40python=2Eorg=5D=FD?= <python-list@python.org>
Subject: RE: Numpy outlier removal
Thread-Topic: Numpy outlier removal
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Date: Mon, 7 Jan 2013 02:12:23 +0000
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Xref: csiph.com comp.lang.python:36339

> In other words: this approach for detecting outliers is nothing more than=
=A0=0A=
=0A=
> a very rough, and very bad, heuristic, and should be avoided.=0A=
=0A=
Heh, very true but the results will only be used for conversational=A0purpo=
ses.=0A=
I am making an assumption that the data is normally distributed and I do ex=
pect=0A=
valid results to all be very nearly the same.=0A=
=0A=
> You can read up more about outlier detection, and the difficulties=A0=0A=
> thereof, here:=0A=
=0A=
=0A=
I much appreciate the links and the thought in the post. I'll admit I didn'=
t=0A=
realize outlier detection was as involved.=0A=
=0A=
=0A=
Again, thanks!=0A=
jlc=