And as we draw more samples, you can see it's not obvious, but our intervals change depending on what our actual sample proportion is, because we use our sample proportion to calculate our confidence interval, because we're assuming whoever's doing the sampling does not actually know the true population proportion. Now, what's interesting here about this simulation is that we can see what percentage of the time does our confidence interval, does it actually contain the true parameter? So let me just draw 25 samples at a time. And so you can see here that right now, 93%, for 93% of our samples, did our confidence interval actually contain our population parameter? And we can keep sampling over here. And we can see the more samples that we take, it really is approaching that close to 95% of the time, our confidence interval does indeed contain the true parameter. And so once again, we did all that math in the previous video, but here you can see that confidence intervals, calculated the way that we've calculated them, actually do a pretty good job of what they claim to do.