The Central Limit Theorem by itself makes the NormalDistribution the most important probability distribution. It statesthat any distribution can be approximated to some extent by thenormal distribution. Specifically, if a sample of size n is takenfrom a population with meanandvariancethenthe sample mean has the approximate distribution The mean and variance of some common distributions of given in thetable below.
Distribution |
Parameters and Meaning of Parameters |
Mean |
Variance |
Approximate Distribution of Sample Mean for Sample of Size n |
-mean –standard deviation |
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Uniform, |
andare the minimum and maximum possible values of the random variable |
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Binomial, |
is the number of trials,is the probability of success |
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Geometric, |
is the probability of success |
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Poisson, |
is the average number of events per time period |
Example: For a sample of size 10 taken from a uniform distribution between the limitsandwhat is the probability that the average is less than 12?
This corresponds to a probability of 0.791.