So in a lot of what we're doing in this inferential statistics, we're trying to figure out what is the probability of getting a certain sample mean. So what we've been doing, especially when we have a large sample size, so let me just draw a sampling distribution here, so let's say we have a sampling distribution of the sample mean right here. It has some assumed mean value and some standard deviation. And what we want to do is any result that we get, let's say we get some sample mean out here, we want to figure out the probability of getting a result at least as extreme as this, so you can either figure out the probability of getting a result below this and subtract that from 1, or just figure out this area right over there. And to do that, we've been figuring out how many standard deviations above the mean we actually are. And the way we figure that out is we take our sample mean, we subtract from that our mean itself, what we assume the mean should be, or maybe we don't know what this is, and then we divide that by the standard deviation of the sampling distribution. This is how many standard deviations we are above the mean, that is that distance right over there.