Author: Dann Corbit
Date: 12:24:31 01/23/04
30 experiments is a fairly standard rule as to when you should start to trust the results for experimental data. From: http://www.twoplustwo.com/mmessay8.html "A good rule of thumb is to have at least 30 observations (playing sessions) for the estimate to be reasonably accurate. However, the more the better, unless for some reason you think the game for which you are trying to estimate your standard deviation has changed significantly over some particular period of time." From: http://www.odu.edu/sci/xu/chapter3.pdf "C. The Reliability of s as a Measure of Precision - the more measurements that are made, the more reliable the value obtained for s. Usually 20 - 30 measurements are necessary." From http://www.stat.psu.edu/~resources/ClassNotes/ljs_21/ljs_21.PPT#11 Concerning the central limit theorem, we have this: Even if data are not normally distributed, as long as you take “large enough” samples, the sample averages will at least be approximately normally distributed. Mean of sample averages is still mu Standard error of sample averages is still sigma/sqrt(n). In general, “large enough” means more than 30 measurements. Of course, the more the merrier, when it comes to measurements.
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