Let's do that 10,000 times. So notice, when you took an n of two, even though we did it 10,000 times, this is not approaching a normal distribution. You can actually see it in the skew and kurtosis numbers. It has a rightward positive skew, which means it has a longer tail to the right than to the left. And then it has a negative kurtosis, which means that it's a little bit, it has shorter tails and smaller peaks than a standard normal distribution. Now, when n is equal to 16, you do the same, so every time we took 16 samples from this distribution function up here and averaged them, and each of these dots represent an average, we did it 10,001 times. Here, and notice, the mean is the same in both places, but here all of a sudden, our kurtosis is much smaller, and our skew is much smaller, so we are more normal in this situation.