For every sample you do for your average, the more you put in that sample, the less standard deviation. Think of the extreme case. If instead of taking 16 samples from our distribution every time, or instead of taking 25, if I were to take a million samples from this distribution every time, if I were to take a million samples from this distribution every time, that sample mean is always gonna be pretty darn close to my mean. If I take a million samples of everything, if I try to essentially try to estimate a mean by taking a million samples, I'm gonna get a pretty good estimate of that mean. The probability that a bunch of the, a million numbers are all out here is very low. So if n is a million, of course, all of my sample means when I average them are all gonna be really tightly focused around the mean itself. And it actually, and so hopefully that kind of makes sense to you as well.