And so instead, what you do is say, well look, okay, I can't get every man, but maybe I can take a sample, I could take a sample of the men in the United States, and I'm going to make an effort, I'm gonna make an effort that it's a random sample. I don't wanna just go sample 100 people who happen to play basketball, or play basketball for their college. I don't wanna go sample 100 people who are volleyball players. I wanna randomly sample, just maybe the first person who comes out of a mall in a random town, or in several towns, or something like that, something that should not be based in any way, or skewed in any way, by height. So you take a sample, and from that sample, you can calculate a mean of at least the sample, and you'll hope that that is indicative of, especially if this was a reasonably random sample, you'll hope that that was indicative of the mean of the entire population. And what you're going to see in much of statistics, in much of statistics, it is all about, it is all about using information, using things that we can calculate about a sample, to infer things about a population, because we can't directly measure the entire population. So for example, let's say, and I wouldn't, if you're actually trying to do this, I would recommend doing at least 100 data points, or 1,000, and later on we'll talk about how you can think about whether you've measured enough, or how confident you can be.