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I understood my task as convincing another _human_ that it was randomly generated. Since N was low for each of the tasks, I was deliberate about sometimes having repeated values, and not ensuring that every option was picked an equal number of times, since that looks suspiciously algorithmic. Apparently I'm over 60.
Earlier quoted context omitted.
They are equally likely, yes. But, the questions here pertain to whether or not an other person would perceive your sequence as random. It wasn't too long ago there was an article on HN (can't find it now) describing what feels random to people. Essentially, a sequence feels more random the harder it is to explain. So, HHHHHHHH doesn't feel random because it's summarized as 8 H's and HTHTHTHT doesn't feel random eith…
But if this is about perceived randomness shouldn’t people also guess which sequence was created by a human vs sequences created by some algorithm? I understand that to score randomness you probably would create n-grams of the characters and look if these would be equally distributed. But for such short sequences it feels hard to do. Maybe a statistician can explain this? For me, using my right thumb on a smartphone…
I would understand if the actual measurement is not perceptual but mechanised, i.e. "how small can we compress this stream of random choices using our best known compression methods" or something. (But then a stream of 10 symbols is surely not enough to show you the humans.)
Earlier quoted context omitted.
They are equally likely, yes. But, the questions here pertain to whether or not an other person would perceive your sequence as random. It wasn't too long ago there was an article on HN (can't find it now) describing what feels random to people. Essentially, a sequence feels more random the harder it is to explain. So, HHHHHHHH doesn't feel random because it's summarized as 8 H's and HTHTHTHT doesn't feel random eith…
But if this is about perceived randomness shouldn’t people also guess which sequence was created by a human vs sequences created by some algorithm? I understand that to score randomness you probably would create n-grams of the characters and look if these would be equally distributed. But for such short sequences it feels hard to do. Maybe a statistician can explain this? For me, using my right thumb on a smartphone…
It's about what the test person think another human will perceive as random so there's a layer of indirection there. If these guesses you suggest would help the study or not I really can't say.
I understood my task as convincing another _human_ that it was randomly generated. Since N was low for each of the tasks, I was deliberate about sometimes having repeated values, and not ensuring that every option was picked an equal number of times, since that looks suspiciously algorithmic. Apparently I'm over 60.
Same reasoning here, and same result.
Hm I'm curious about the complexity measurement for the coin tosses. How does it work? There is suspicious clustering in the plot, at complexity slightly lower and higher than -1. Complexity -1 is also more sparse than seems reasonable from the shape/density of the cloud.
I'm also curious about this. Randomness doesn't actually look very random. There's a surprising number of repeated characters.
It's maybe not so counter-intuitive as the Birthday paradox, but maybe already showing how bad our intuition is at grasping randomness. Initially I had hoped about research on that, which is probably very hard. - Or not? Couldn't you look at the n-gram distributions of the data and look how much that is "random", i.e. are people avoiding clusters harder than they should?
I understood my task as convincing another _human_ that it was randomly generated. Since N was low for each of the tasks, I was deliberate about sometimes having repeated values, and not ensuring that every option was picked an equal number of times, since that looks suspiciously algorithmic. Apparently I'm over 60.
Same reasoning here, and same result.
For any experimental science, the integrity of experiment (thus reliability of data) is important. For experiments with human subjects, the question is whether the subjects answered the questions in good faith. A sequence like 'HHHHHHHHHH' for the coin toss experiment looks like an answer in bad faith; it is mechanically easy to keep pressing the same button, and a subject is unlikely to think that such a sequence is a likely random sequence. Therefore, the replicating authors are fully justified to eliminate those poor faith answers. The original paper authors' claim that 'HHHHHHHHHH' is as equally probabilistic as any other sequence is irrelevant.
Edited for clarity.
Yeah... you thought I was 60. Seems from the comments this is a common thing.
You might want to check your algorithms. But then again, you do say in the end of the results that you need more 60+ year olds to help make this more accurate.
Also, a bone to pick. You claim that people get less random as they get older over 25, with 25 being the peak. I would wonder if maybe that has some correlation with the brain finally fully developing from adolescents into true/full adulthood. (Remember folks, we do call people 'young adults' for a while in their 20's.)
Also, while you make that claim about people as they get older, I still managed to get a coin flip result that was 13% more random than others at my age group of 33. Or something like that. I forget how it was worded exactly off hand this moment without going and checking again in my history. My point here is this.
If randomness declines with age past 25, but my score at age 33 is 13% more random than others in the same age range; then is it truly declining for everyone equally or is it just some people more rapidly than others?
I think this maybe correlates potentially with the findings of the trend disappearing once the non-random data is removed. (The all heads/all tails results.)
Anyways. With all this said, I do agree you need some more participants above the age of 60. Have you considered using facebook at all?
Earlier quoted context omitted.
I think that's their point. Since there isn't an actual correlation, their guess is basically 50/50.
But if their guess is 50/50, that is from a subset that is mostly under-60's, which presumably means that they have evidence for the opposite? (i.e. there is no statement that the 51% figure is age adjusted) I'm probably just being silly here...