Guides to randomness
The ideas behind the tools on this site, explained with the sources they rest on.
A random result is only as good as the way it was made and the way it is used. These guides cover both: where computers get their randomness and why a cryptographic generator is unpredictable in practice, how turning random bits into a range or a shuffled list can quietly favour some outcomes, what careful experiments with thousands of real coin tosses found, and how to run a prize draw so that entrants can see it was fair.
Each guide lists the standards, papers and official documents it relies on, and links to the tools that put the method into practice.
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True random and pseudo-random numbers
How physical random sources, seeded pseudo-random generators and cryptographic generators differ, what the NIST standards cover, and which one this site uses.
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How to run a fair random draw
Freeze and clean the entry list, settle entries and prizes in advance, draw once with a timestamp, handle ineligible winners and keep the evidence.
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Is a coin toss really 50/50?
A tossed coin lands on the side it started about 51% of the time. What the physics and 350,757 recorded flips show, and why spinning a coin is worse.
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Fair shuffling and modulo bias
Why the remainder trick favours some numbers, how rejection sampling and the Fisher–Yates shuffle fix it, and how two common shuffles go wrong.