The population distribution for y divided by m. And so once again, I'll just write this out front. This is the variance of the differences of the sample means. And if you wanted the standard deviation of the differences of the sample means, you just have to take the square root of both sides of this. If you take the square root of this, you get the standard deviation of the difference of the sample means is equal to the square root of the population distribution of x, or the variance of the population distribution of x divided by n plus the variance of the population distribution of y divided by m. And then the whole reason why I've even done this, and this is just neat because it kind of looks a little bit like a distance formula. And I'll kind of throw that out there as we get more sophisticated with our statistics and try to visualize what all of this kind of stuff means in more advanced topics. But the whole point of this is now we can make inferences about a difference of means. If we have two samples and we want to say, and we take the means of both of those samples and we find some difference, we can make some conclusions about how likely that difference was just by chance.