I've been reading a book on the philosophy of statistics, and what is interesting is that the statistical community has been, historically, completely divided on that question.
The only thing they agree on is the equations. Once you ask the question of "and what situation are we facing in the real world" consensus starts to break down.
Interestingly, the core of probability - the "Random Variable" is almost completely unobservable in the world of science. Everything in classical mechanics turned out to be deterministic. The parts that were grappled with statistics were probably not random effects, but unpredictable deterministic effects. For example, the measurement errors could be treated as random variables, but ultimately were not expected to be random in cause.
Compare this to geometry and algebra, where I would argue it is easier to find a 'real' example right from the get go. Opinions, obviously, vary.
Cipher text can look a lot like randomness to the uninformed observer. If a deterministic system produces results, but the observer cannot model the underlying process from the results, are those results now random?
> "Bell's theorem rules out local hidden variables as a viable explanation of quantum mechanics (though it still leaves the door open for non-local hidden variables, such as De Broglie–Bohm theory, etc)"
Yeah, but there is an important subtlety. Quantum mechanics has a bunch of things that can be /modeled extremely well/ by random variables. But it might still turn out that that they are deterministic in some complicated way.
Then we would be back in a universe where we have an extremely useful concept in the humble random variable, and no examples of anything that is fundamentally random. If I start with a random variable, I couldn't reasonably approximate it with a real phenomenon, because the phenomenon would be deterministic.
Compare that to a line - I can define a line between the center of mass of my two hands. We can quibble all day about whether that is a well defined definition (I suppose it isn't), but if I wanted to approximate a real line with two points in space I could.
I contend this is an interesting an important difference between subjects like geometry and subjects like statistics. The underpinnings of statistic are _extremely_ philosophical.
Statistical Thought - A Perspective and History (Shoutir Chatterjee). I'm really enjoying it, quite approachable at an undergraduate level of mathematics.
The only thing they agree on is the equations. Once you ask the question of "and what situation are we facing in the real world" consensus starts to break down.
Interestingly, the core of probability - the "Random Variable" is almost completely unobservable in the world of science. Everything in classical mechanics turned out to be deterministic. The parts that were grappled with statistics were probably not random effects, but unpredictable deterministic effects. For example, the measurement errors could be treated as random variables, but ultimately were not expected to be random in cause.
Compare this to geometry and algebra, where I would argue it is easier to find a 'real' example right from the get go. Opinions, obviously, vary.