[HN Gopher] What Every Experimenter Must Know About Randomization
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What Every Experimenter Must Know About Randomization
Author : underscoreF
Score : 29 points
Date : 2026-02-18 19:02 UTC (3 hours ago)
(HTM) web link (spawn-queue.acm.org)
(TXT) w3m dump (spawn-queue.acm.org)
| Tomte wrote:
| Starts interesting, then veers into the usual "true random
| number" bullshit. Use radioactive decay as source of your random
| numbers!
| amelius wrote:
| How do we know it's truly random?
| ChadNauseam wrote:
| The only known explanation of what's going on in quantum
| mechanics is a multiversal one^[1]. Using radioactive decay
| of an atom as an example: there are an uncountably infinite
| number of universes that are initially "fungible" (identical
| in every way), and over time the universes gradually
| differentiate themselves with the atom going from a non-
| decayed to decayed state, at different times in each
| universe. But you will be in all of those universes. So if
| you thought the atom would decay in, let's say 5 seconds,
| there would be some universes where you were right and some
| where you were wrong. That makes it impossible to ever make
| reliable specific predictions about when the atom will decay.
| So, in practice that just looks like perfect randomness.
|
| ^[1]: There are other interpretations, of course. And those
| other interpretations are equally explanatory. But they do
| not claim to be explanations of what is actually happening to
| unobserved quantum particles. There is also Bohmian
| mechanics, but I don't know how many people take it
| seriously.
| zeroxfe wrote:
| > usual "true random number" bullshit
|
| What's bullshit about it? This is how TRNGs in security
| enclaves work. They collect entropy from the environment, and
| use that to continuously reseed a PRNG, which generates bits.
|
| If you're talking "true" in the philosophical sense, that
| doesn't exist -- the whole concept of randomness relies on an
| oracle.
| wtallis wrote:
| I don't think hardware random number generators are bullshit,
| but it's easy to overstate their importance. Outside of
| cryptography, there aren't a whole lot of cases that truly
| _require_ that much care in how random numbers are generated.
| For the kind of examples the article opens with (web page A
| /B testing, clinical trials, etc.) you'll never have sample
| sizes large enough to justify worrying about the difference
| between a half-decent PRNG and a "true" random number
| generator.
| wavemode wrote:
| What PRNGs lack compared to TRNGs is security (i.e.
| preventing someone from being able to use past values to
| predict future values). It's not that they somehow produce
| statistically invalid results (e.g. they generate 3s more
| often than 2s or something). Unless they're very poorly
| constructed.
| refsys wrote:
| Maybe people have bad memories from linear congruential
| generators, these could go really bad
| (https://en.wikipedia.org/wiki/Marsaglia%27s_theorem)
| BigTTYGothGF wrote:
| "If N = 300, even a 256-bit seed arbitrarily precludes all but an
| unknown, haphazardly selected, non-random, and infinitesimally
| small fraction of permissible assignments. This introduces
| enormous bias into the assignment process and makes total
| nonsense of the p-value computed by a randomization test."
|
| The first sentence is obviously true, but I'm going to need to
| see some evidence for "enormous bias" and "total nonsense". Let's
| leave aside lousy/little/badly-seeded PRNGs. Are there any non-
| cryptographic examples in which a well-designed PRNG with 256
| bits of well-seeded random state produces results different
| enough from a TRNG to be visible to a user?
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