Randomness is Random - Numberphile on HackerTube: recommended by 4 Hacker News commenters across 4 separate months, 2019–2022.
explainer · evergreen
Numberphile with Simon Pampena on how humans misunderstand randomness, including coin-flip sequences, run lengths and the gambler's fallacy.
Recommended as an accessible demonstration that people are bad at producing or judging random sequences.
“Here's a great video demonstrating how people tend to misunderstand randomness”
4 Hacker News comments link this video. Each one links back to its thread.
This may indirectly answer your question: ▶ this video TLDW: We don't pick numbers at random. At all. We're so bad at it that you can make money off this fact.
in “Some neurons are active when adding, others when subtracting” · View on HN
Oh, I remember good old fallout 1-2 when you have 42% hit chance but still miss 7 times in a row. There is also a good Numberphile video on what we think random really is (it is not) ▶ this video
in “A New Algorithm for Controlled Randomness” · View on HN
I would argue that the problem with frequentist statistics is that it aligns with humans' flawed intuition of how randomness works. People are inherently obsessed with finding patterns to support their hypotheses. The problem is that what we perceive as random and extremely unlikely events are in fact much more probable than what we estimate from using Gaussian methods. And the frequentist approach helps to create this distortion by ignoring black swans. Here's a great video demonstrating how people tend to misunderstand randomness: ▶ this video
in “Interview on ”Bayesian Statistics the Fun Way”” · View on HN
There is a very accessible "numberphile" video which I think is closely related to this, about playing the odds on predicting elements of a nominally-random coin-flip sequence using the expected run length. ▶ this video
in “Perceptions of Randomness: Why Three Heads Are Better Than Four (2009) [pdf]” · View on HN