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. But when our sample size was larger, our standard deviation became smaller. In fact, our standard deviation became smaller than our original population distribution, so let me, or our original probability density function. Let me show you that with a simulation.