And so the key is is to figure out the P value. What is the probability of getting a result this much above the assumed proportion or greater, at least this much above the assumed proportion if we assume that the null hypothesis is true? And if that probability, if that P value is below a preset threshold, if it's below our significance level, they haven't told it to us yet, it looks like they're gonna give some in the choices, well, then we would reject the null hypothesis, which would suggest the alternative. If the P value is not lower than this, then we will fail to reject the null hypothesis. Now, to calculate that P value, to calculate that probability, what we figure out is, well, how many, in our sampling distribution, how many standard deviations above the mean of the sampling distribution, and the mean of the sampling distribution would be our assumed population proportion, how many standard deviations above that mean is this right over here? And that is what this test statistic is. And then we can use this to look at a z-table and say, all right, well, in a normal distribution, what percentage or what is the area under the normal curve that is further than 1.84 standard deviations or at least 1.84 or more standard deviations above the mean?