> Edit: One important thing the article doesn't talk about is how sperm is actually counted. Obviously researchers don't count all 150 to 300 million sperms per sample; they probably count a small (or very small) sub-sample and extrapolate
When you've got hundreds of millions of something distributed essentially randomly in some space, counting a subsample and extrapolating is fine.
> If for example, they did rough extrapolations in the 50s, and then in the 90s they were able to do an exact and exhaustive count, it's a problem.
That's not a change that's happened, smaller volumes are still analysed, but no that's not necessarily a problem.
At such scales, "small" samples can be totally fine and have an extremely high chance of matching a complete analysis. That's why polling and sampling works.
The problem shrinks even more when you're looking at averages over groups. Smaller samples are noisy, not biased. Averaging over many doesn't lower bias but it does lower the noise.
When you've got hundreds of millions of something distributed essentially randomly in some space, counting a subsample and extrapolating is fine.