2000 converges well, so 2000 different samples of 100 tosses are used. Step 2: Choice of number of Sessions: 50 sessions is never sufficient, even with huge sample sizes in the millions. Step 1: Choice of sample size: 100 tosses / bits. 50-50 is not the expected value of the ordered bins, so this test is superior to any frequency test that instead expects 50-50. When coins are flipped 100 times, the expected values are 53.9795 of one and 46.0205 of the other, sometimes more heads, sometimes more tails. This test subsumes any frequency test that expects 50-50 because it is more stringent.ĭefinitions: t= tosses / trials b=bins / urns s=sessions of tosses n=sets of sessionsīecause coin tosses are usually not 50-50, this new test can be utilized with great effectiveness using a pool of 40,000,000 bits. That said, described here is a simple effective new Ordered Frequency Test for bits. We actually don't need too many RNG tests because many "subsume" one another. Ī note about testing a Random Number Generator: The preliminary test for any RNG is the Monobit test used by the NIST which simply counts the number of 1s and 0s.
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Embrace the element of surprise, break free from design constraints, and let our generator spark your imagination.Here is a detailed explanation of how to start.
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