Question 193975
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Let *[tex \LARGE X_1, X_2, X_3, ... X_n] be a sequence of n independent and identically distributed (i.i.d) random variables each having finite values of expectation *[tex \LARGE \mu] and variance *[tex \LARGE \sigma^2 >0]. The central limit theorem states that as the sample size n increases, the distribution of the sample average of these random variables approaches the normal distribution with a mean *[tex \LARGE \mu] and variance *[tex \LARGE \frac{\sigma^2}{n}] irrespective of the shape of the original distribution.







John
*[tex \LARGE e^{i\pi} + 1 = 0]
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