Quote:
[Thu Feb 14 08:48:30 2013] Ghwerig says, 'I think central limit theorem just says that for any large sample size of independent events/variables that it tends to go like a normal distribution about the mean'
[Thu Feb 14 08:49:11 2013] You say, 'this is correct but'
[Thu Feb 14 08:49:19 2013] You say, 'i thought it also said somethinga bout the rate of convergence'
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The Central Limit Theorem states:
The sample mean of a large random sample of random variables with mean μ and finite variance σ² has approximately a normal distribution with mean μ and variance σ²/n.
It does not address convergence because not all instances have the same rate of convergence. The fact is that the drop rates are not identical, so this situation is not iid. To get a 'standard normal distribution', you need to use another variable, (X - μ)/σ.