Talk:Random number generation

Randomness is an observed entity

The article starts out with: "A random number generator (RNG) is a computational or physical device designed to generate a sequence of numbers or symbols that lack any pattern, i.e. appear random." But it should be the other way around: If an Observer find that a sequence lack any pattern, it appears random to him. Different observers may rate the same sequence differently. The randomness is not in the sequence.

Bo Domstedt http://www.trng98.se

Random number generation input through analogue computer filtering as an attractor which shapes the range of the output*

write about it please

Defects of simple algorithms

@Aezarebski: Thank you for adding a reference to Nishimura's work. However, I do not quite understand how this work is relevant to this section. [1] contains some language on p. 5, but I have hard time interpreting it to support the sentence "are unsuitable where high-quality randomness is required, such as ... statistics" (ellipsis is mine). Can you help me? Dimawik (talk) 06:13, 25 June 2024 (UTC)

Thanks for following up on this. If you use a poor quality PRNG, some statistical methods will produce poor results (e.g. over/underestimating variance). Many algorithms are not very sensitive to this, so often it doesn't matter. However, the cost of using a good one is not very high, so the rule of thumb is to use a decent one to be safe. I haven't been able to find a good reference spelling this out though. (Maybe this? http://www0.cs.ucl.ac.uk/staff/d.jones/GoodPracticeRNG.pdf)

I think the cleanest solution would be to remove the "statistics" part and just keep the "cryptography" part, for which a good quality PRNG is clearly important. Aezarebski (talk) 10:56, 25 June 2024 (UTC)

Computational methods?

The section on computational methods needs to be rewritten - or replaced by an {{excerpt}} of the Pseudorandom number generation. There are multiple solid ways to design a DRBG (which is essentially what is described in the section) with output being statistically indistinguishable from a true random sequence. Most methods described in this section are very primitive, the reason for their use is either historical or practical - or they are not actually used - so the statements that true random numbers are superior (without explaining what "are not as random as numbers generated from electromagnetic atmospheric noise" can actually mean) are misplaced. All this was kind of supported by the non-RS (or links to texts that contained no such statements) that I have removed. Dimawik (talk) 18:41, 24 October 2025 (UTC)