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Subject: Small sample sizes. Why not use biostatistics?

Author: J. C. Boco

Date: 12:31:26 06/30/02

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In the above thread (which I only perused) there is the complaint of the small
sample of games played.  I agree of course.  I just have a question about the
statistics used.

First of all, I bet that most people on these boards has taken at least a basic
statistics course.  So have I.  Sample sizes were always large when theory was
being taught, often N was 500 or more.  In most fields of endeavor, this is
enough.

When an undergrad in biochemisty, I had to take a particularly leathal class
called "Biostatistics".  This is a mathamatically rigorous discipline.  The
purspose of this branch of statistics is to draw meaningful conclusions based on
small sample sizes inherent in live animal experiments (after all, the upkeep
and experimentation on rats is expensive--let along "higher" animal models.

This stuff was nasty.  Sample sizes of less than 25 were the norm.  There was
awful, nested levels of analysis which was used to combine several different
environmental conditions without having to replicate experiments in each of the
different conditons.  I took this class over 7 years ago and have had no need
for it since, so I really cannot be more lucid in my description than this, and
most certainly could not give meaningful suggestions on how to perform a
nested-analysis of variance for ssdf data (other than saying that a round-robin
type of tournament would probably avail itself into a nested biostatistics
analysis.)

I have typed too much already.  All that text above was pretty much to set up
the simple question:  Is anyone at the SSDF aware of biostistics.  If so is
there a reason you don't use it?  (Since it has been many many years since I've
studied it, perhaps there is a trivial reason for this I don't remember).

It's my perception that very few people who study the life science really get
into computer chess, and therefore the branch of biostatistics is unknown to the
SSDF.




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