Hypergeometric Distribution
A discrete random variable X is said to have a hypergeometric distribution if its probability density function is defined as,
where N is a positive integer , M is a nonnegative integer that is at most N and n is the positive integer that at most M. If any distribution function is defined by the following probability function then the distribution is called hypergeometric distribution.
Properties of Hypergeometric Distribution
 Hypergeometric distribution tends to binomial distribution if N➝∞ and K/N⟶p.
 Hypergeometric distribution is symmetric if p=1/2; positively skewed if p<1/2; negatively skewed if p>1/2.
 The mean of the hypergeometric distribution concides with the mean of the binomial distribution if M/N=p.










 The hypergeometric distribution is commonly studied in most introductory probability courses. In introducing students to the hypergeometric distribution, drawing balls from an urn or selecting playing cards from a deck of cards are often discussed. This is a simple process which focus on sampling without replacement.
 We are also used hypergeometric distribution to estimate the number of fishes in a lake.
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