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Central Limit Theorem and Normal Distribution EE3060 Probability Yi-Wen Liu November 2010.

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Presentation on theme: "Central Limit Theorem and Normal Distribution EE3060 Probability Yi-Wen Liu November 2010."— Presentation transcript:

1 Central Limit Theorem and Normal Distribution EE3060 Probability Yi-Wen Liu November 2010

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3 Binomial approximated by normal distributions N=25 N=50 N=100

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9 Binomial, now approximated by normal distributions N=25 N=50 N=100

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15 Binomial, now approximated by normal distributions N=25 N=50 N=100

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21 Review: Binomial(40,p) with Poisson Approximation

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31 Conclusions Recall that binomial(N,p) is an independent sum of N Bernoulli r.v.’s N ↑, Central Limit Theorem applicable, Gaussian fits better and better –True for all p –Useful because, for large N, N! cannot be calculated by Matlab double-precision floating point


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