A moment generating function does exist for the hypergeometric distribution.
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The standard normal distribution has a mean of 0 and a standard deviation of 1.
A small partial list includes: -normal (or Gaussian) distribution -binomial distribution -Cauchy distribution
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NBCUniversal Television Distribution was created in 2004.
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The binomial distribution is a discrete probability distribution which describes the number of successes in a sequence of draws from a finite population, with replacement. The hypergeometric distribution is similar except that it deals with draws without replacement. For sufficiently large populations the Normal distribution is a good approximation for both.
The MGF is exp[lambda*(e^t - 1)].
J.H Chung has written: 'Confidence limits for the hypergeometric distribution' -- subject(s): Sampling (Statistics)
J. H. Chung has written: 'Confidence limits for the hypergeometric distribution' -- subject(s): Sampling (Statistics)
In my time with working with computers, I have never heard of MGF before. MGF is a car and something to do with finance but thats about it.
hypergeometric distribution: f(k;N,n,m) = f(5;52,13,5)
Using the hypergeometric distribution, the answer is 2114/3003 = 0.7040
with replacement: binominal distribution f(k;n,p) = f(0;5,5/12) without replacement: hypergeometric distribution f(k;N,m,n) = f(0;12,5,5)
W. N. Bailey has written: 'Generalized hypergeometric series' -- subject(s): Hypergeometric series
Wenchang Chu has written: 'Basic almost-poised hypergeometric series' -- subject(s): Hypergeometric series
Bernard M. Dwork has written: 'Generalized hypergeometric functions' -- subject(s): Hypergeometric functions