Let's say we start with this crazy distribution up here. It really doesn't matter what distribution we're starting with. We saw in the simulation that when n is equal, let's say n is equal to five, our graph after we try, we take samples of five, average them, and we do it 10,000 times, our graph looks something like this. It's kind of wide like that. And then when we did n is equal to 10, our graph looked a little bit, it was actually a little bit squeezed in like that, a little bit more. So not only was it more normal, that's what the central limit theorem tells us because we're taking larger sample sizes, but it had a smaller standard deviation or a smaller variance, right? The mean is gonna be the same either case.