Does anyone know or can expand on what I'm talking about?
Does anyone know or can expand on what I'm talking about?
Also for benford's law to show up you want your data to span several orders of magnitude (so e.g. you have numbers in tens, hundreds and thousands) and for a datapoint to be about as likely to give an n-digit number as a n+1-digit number, not everywhere and not exactly but it needs to dominate over there being ten times times as many of them with each step.
> Benford's Law tends to be most accurate when values are distributed across multiple orders of magnitude, especially if the process generating the numbers is described by a power law (which is common in nature).
If you're dealing with signed integers, you'll have an even more lopsided distribution in favor of 1 for both 8-bit and 32-bit numbers (assuming you don't count the negative sign). And of course, all of this is assuming base ten; you can make things even more uniform by using binary!
thank you for the good, concise, starter breakdown of why this is a feature of decimal math.
I've spent a lot of time thinking about random numbers, and how to pull random booleans out of pseudo-random numbers. No one would ever choose UUIDs to serve as a source of randomness. But the observation that "4" comes out really often in UUIDs is on par with the observation that you can't just take the first digit of a 32-bit unsigned, un-padded random number and expect it to be an equally weighted random between 1 and 9. Right? So doesn't that relate?