Here we took the sample mean every time, but you could have also taken the sample sum. The central limit theorem would have still applied. But that's what's so super useful about it. Because in life, there's all sorts of processes out there, proteins bumping into each other, people doing crazy things, humans interacting in weird ways, and you don't know the probability distribution functions for any of those things. But what the central limit theorem tells us is that if we add a bunch of those actions together, assuming that they all have the same distribution, or if we were to take the mean of all of those actions together, and if we were to plot the frequency of those means, we do get a normal distribution. And that's frankly why the normal distribution shows up so much in statistics, and why, frankly, it's a very good approximation for the sum or the means of a lot of processes. Normal distribution.