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Subject: Re: Petir 1.7 vs Ufim 501 ended 11 to 9

Author: Dann Corbit

Date: 12:06:21 10/13/04

Go up one level in this thread


On October 13, 2004 at 09:08:19, Norm Pollock wrote:

>On October 12, 2004 at 16:29:52, Dann Corbit wrote:
>
>>On October 12, 2004 at 14:50:51, Jorge Pichard wrote:
>>
>>>Petir 1.7 was using the WizardLight8 Opening book :-)
>>>
>>>Rank	Engine	Score	         Uf      Pe		         S-B
>>>1	Petir 1.7	11.0/20	 · ·· ·· 00011=01=1011=01110=	 99.00
>>>2	Ufim501 	9.0/20	 11100=10=0100=10001=·· ·· ·	 99.00
>>>
>>>
>>>20 games played / Tournament finished
>>>Tournament start: 2004.10.10, 20:52:20
>>>Latest update: 2004.10.12, 18:41:28
>>>Site/ Country: S0025128408, United States
>>>Level: Blitz 15/1
>>>Hardware: AMD Athlon(tm) Processor 1202 MHz
>>>Operating system: Microsoft Windows 2000 Build 2195
>>>PGN-File: C:\Program Files\Arena\Arena.pgn
>>>Table created with: Arena 1.092
>>
>>If you were to add 10 more games so that your tournaments had 30 games each, the
>>statistical significance goes up quite a bit.
>>
>>30 is a sort of magic number when it comes to statistical measurements.
>
>I remember the "magic number" as 32. It sort of allows the use of a normal
>distribution to approximate a binomial distribution. Something like that.

Well, if 30 is good, then 32 would be fractionally better, of course.

From here:
http://www.proaxis.com/~johnbell/sfpp/sfpp6.htm
We have this:
"Luckily, some nice person has figured this out, and published another table
called the "t-table". It is very close to the Z-table except in the very small
sample sizes. In fact, after a sample size of about 30 or so there is virtually
no difference (which just means that you are now getting a very good estimate of
the standard deviate). You often hear in statistics that "after a sample size of
30 it is correct to use the Z-table". This isn't really true, but there is so
little difference between the tables that nobody worries about doing it."

From here:
http://www.jsc.nasa.gov/bu2/PCEH/PCEH-D.DOC
We have this:
"There is one complication with this result.  To be able to judge the size of
the error we might make when we use   as an estimate of  , we must know the
value of the population standard deviation,  .  Since this is not the case in
most practical situations, we have no choice but to replace   with an estimate,
usually the sample standard deviation, s.  In general, this is considered to be
reasonable provided the sample is sufficiently large (n >= 30)."

Other citations for 30:
http://home.xnet.com/~fidler/triton/math/review/mat170/ssmean/ssmean1.htm
http://qudata.com/online/statcalc/
http://arnoldkling.com/apstats/ttests.html
http://www.bized.ac.uk/timeweb/digging/dig_source_illus.htm
http://instructional1.calstatela.edu/mfinney/Courses/309/note.html

At any rate, good things start to happen when you have 30 or more observations.
And when you have significantly less than 30 observations, you should use the T
test tables (or perform the integration yourself).



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