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Central limit theorem (view source)

Revision as of 18:33, November 26, 2015

322 bytes added ,  18:33, November 26, 2015
If the sample size is only one, then the distribution of the average of samples will not approach a Normal distribution, but will approach the distribution of the underlying probability function.
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The '''central limit theorem''' is a fundamental theorem in statistics.  It states that:
 
The '''central limit theorem''' is a fundamental theorem in statistics.  It states that:
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:the distribution of an average of samples, taken from ''any''' type of underlying probability function, with approach a [[Normal distribution]] as the sample size increases.
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:the distribution of an average of samples, taken from ''any''' type of underlying [[probability function]], will approach a [[Normal distribution]] as the sample size increases.
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If the sample size is only one, then the distribution of the average of samples will not approach a [[Normal distribution]], but will approach the distribution of the underlying probability function.  But as the sample size increases, the distribution of their averages increasingly approaches a Normal distribution.
 
[[category:Probability and Statistics]]
 
[[category:Probability and Statistics]]
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