Author: Dann Corbit
Date: 15:33:52 01/23/04
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On January 23, 2004 at 18:20:34, Russell Reagan wrote: >On January 23, 2004 at 15:24:31, Dann Corbit wrote: > >>30 experiments is a fairly standard rule as to when you should start to trust >>the results for experimental data. > >So what does this mean for chess engine matches? You need at least 30 games? Or >30 matches? If matches, how do you determine how long each match should be? It means less than 30 games and you cannot trust the answer. With more than 30 games, confidence rises. I bring up the number 30 because it is important in this case. If you run (for instance) a 15 game contest, it would be dangerous to try to draw conclusions from it. With 30 games or more, even something that does not perfectly model a normal distribution will start to conform to the right answers (e.g. the mean calculation will be about right. The standard deviations will be about right unless sharply skewed). 30 games is the break even limit where deficiencies in the choice of a normal distribution as a model start to become smoothed over.
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