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- Newsgroups: sci.math.stat
- Path: sparky!uunet!centerline!noc.near.net!news.cs.brandeis.edu!binah.cc.brandeis.edu!MOKABA
- From: mokaba@binah.cc.brandeis.edu
- Subject: Re: Fwd: Standard Deviation.
- Message-ID: <1992Aug17.215753.6932@news.cs.brandeis.edu>
- Sender: news@news.cs.brandeis.edu (USENET News System)
- Reply-To: mokaba@binah.cc.brandeis.edu
- Organization: Brandeis University
- References: <1992Aug14.172833.11844@cbfsb.cb.att.com> <seX2yRq00Uh785H2EB@andre,<1992Aug14.231916.23479@magnus.acs.ohio-state.edu>
- Date: Mon, 17 Aug 1992 21:57:53 GMT
- Lines: 38
-
- In article <1992Aug14.231916.23479@magnus.acs.ohio-state.edu>, regeorge@magnus.acs.ohio-state.edu (Robert E George) writes:
- >
- >
- .>> (LOTS OF INTERESTING STAFF DELETED TO PRESERVE SPACE)
-
- >I'm not certain what "underestimate" means here: if you are speaking of
- >bias (bias being the difference between the estimand and the expected
- >value of the estimator), then
- >
- > --- _ _
- > \ | X - Xbar |2
- >T = / |_ _|
- > ---
- > ------------------
- > n
- >
- >will "underestimate" the population variance *for any sample size n*.
- >T will always have a negative bias *regardless of how large a sample is
- >used to compute T*.
- >
- >More intuitively, if we take a very sample, we are less likely to get
- >extreme values and so our notion of what the population variance is (note
- >that I am not proposing some particular estimator) will be unrealistic.
- >For instance, I give an exam to two students. Their scores are 67 and
- >71. I think, "Gee, there's not a lot of variability in these scores."
- >But then 8 more students take the exam:
- > 60 78 100 38 50 88 99 39
- >
- >and it now is clear there *is* more variability in these scores.
- >
- >But let me reiterate that T will *always* have a negative bias for the
- >population variance whatever the sample size is
-
- MY IGNORAMUS QUESTION? Does't that negative bias decrease as the sample
- size approaches population size?
-
- thanks in anticipation for answering my question.
- Mokaba
-