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Random Numbers

  1. Hypergeometric Distribution ( - Stanton)
      "The hypergeometric distribution arises when a random selection (without repetition) is made among objects of two distinct types." "The hypergeometric distribution is described by three parameters: N, the total number of objects; R, the number of objects of the first type; and k the number of objects to be chosen. The probability function f(x) is f(x) = C(R,x)*C(N-R, k-x) / C(N,k) for x=max(0,k+R-N)..min(R,k)."

  2. Random Numbers (
      Provides descriptions and definitions of key terms and a random table of 300 digits.

  3. Tests of Random Numbers Generators (
      "Test results are usually reported as a chi2 measure. A chi2 measure of +-2 is probably random noise, +-3 probably means the generator is biased, and +-4 almost certainly means the generator is biased."

      "The best way to test if a generator is good enough for an application is to run the application with two very different generators and see if they produce the same result. The next best way is run the generator's random number sequence through random number tests, like DIEHARD or chi.c or est.c (described below). The sequence tested has to be at least as long as the sequence of random numbers your application plans to use, otherwise the biases your application may encounter can't be caught by the test."


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