The hyper-geometric distribution is a discrete probability distribution which is similar (in some respects) to the binomial distribution. Suppose you have a population of N which contains R successes. The Binomial describes the probability of r successes in n draws out on N with replacement.
However, in many situations the draw is not replaced. In this case you get the hyper-geometric distribution.
The function is given by:
Prob(r successes in n draws out of N) = RCr/[N-RCn-r * NCn]
With the binomial distribution the probability of success remains constant (=R/N) throughout. With the hypergeometric, the numerator for success reduces by one after each successful outcome whereas the denominator reduces by one whatever the outcome.
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The probability is 0.The probability is 0.The probability is 0.The probability is 0.
The probability is 1.The probability is 1.The probability is 1.The probability is 1.
For any event A, Probability (not A) = 1 - Probability(A)
They are both measures of probability.
The probability is 1/2.The probability is 1/2.The probability is 1/2.The probability is 1/2.