3 ms·
That doesn't really tell us anything about variance. After all, in that single trial of generating 347 numbers, his computer could just as easily have spat out
by teaspoon 16y ago
That doesn't really tell us anything about variance. After all, in that single trial of generating 347 numbers, his computer could just as easily have spat out a uniform distribution.*
To see variance, it would have been better to generate 347 numbers many times over, then plot the standard deviation of the count of each number using error bars.
*You can't actually evenly distribute 347 trials over the range [1,20], but you see my point.
- ugh 16y agoThat wouldn’t be as intuitive. We have better statistical tools, sure, but his graph was immediately understandable, even if you don’t know what standard deviation is or what error bars are. I would use that graph as an illustration for the uninitiated even if I had exhausted the statistical toolset. (Also, there are better tools but it’s not as though what he did was meaningless and provided no evidence for the point he was making. It’s not as strong but it is there.)
- ez77 16y agoAnd of course, there is the small probability that his computer could have picked the number 10 as many as 347 times in a row. Something tells me he would have run the computer simulation again in that case.
- DougBTX 16y agohis computer could just as easily have spat out a uniform distribution But that's the point, isn't it? An exactly even distribution is unlikely. So unlikely, that the first distribution he found was probably fine for use in the article. I suppose my only real point here is that error bars are boring, and it's perfectly possible to understand what the variation in a typical random set is by looking at the set, without having to explicitly put error bars around a straight line.