When the population is finite and the sampling is done without replacement, so that the events are stochastically dependent, although random, we obtain hypergeometric distribution. Consider an urn with N balls, M of which are white and N-M are red. Suppose that we draw a sample of n balls at random ( without replacement) from the urn, then the probability of getting k white balls out of n, (k <n) is
A discrete random variable x is said to follow the hypergeometric distribution if it assumes only non-negative values and its probability mass function is given by
P(X =k) =h(k;N,M,n) = k =1,2,….,min(n,M).
= 0 otherwise
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