And remember, the mean of the sampling distribution is going to be the population proportion. So here, we got this sample statistic, this sample proportion. The difference between that and the assumed proportion, remember, when we do these significance tests, we try to figure out the probability assuming the null hypothesis is true. And so when we see this P sub zero, this is the assumed proportion from the null hypothesis. So that's the difference between these two, the sample proportion and the assumed proportion. And then you'd wanna divide it by what's often known as the standard error of the statistic, which is just the standard deviation of the sampling distribution of the sample proportion. And this works out well for proportions because in proportions, I can figure out what this is.