> OpenRouter performs internal categorization on a random sample comprising approximately 0.25% of all prompts
How can you arrive at any conclusion with such a small random sample size?
[^1] This is a simplification. I should say that it depends on the standard error of your statistic, i.e, the thing you're trying to measure (If you're estimating the max of a population, that's going to require more samples than if you're estimating the mean). This standard error, in turn, will depend on the standard deviation of the dimension you're measuring. For example, if you're estimating the mean height, the relevant quantity is the standard deviation of height in the population.
For example, even 300 really random people is enough to correctly assertain the distribution of population for some measurement (say, some personality feauture).
That’s the basis of all polls and what have you
(OK, on rereading, you did link to a WP article about CLT, so 30 it is!)
300 — I had in memory as a safe bet in a case of some skewed stuff like log-normal, exponential, etc.
[1] https://stats.stackexchange.com/questions/166/how-do-you-dec...