So instead, we'll say, okay, let's take our sample mean, plus or minus z star, times the sample standard deviation of our sample, which we can calculate, divided by the square root of n. Now this might seem pretty good if we're trying to construct a confidence interval for our sample, for our mean. But it turns out that this is not, not so good. Because it turns out that this right over here is going to actually underestimate the actual interval, the true margin of error you need for your confidence level. And so that's why statisticians have invented another statistic. Instead of using z, they call it t. Instead of using a z table, they use a t table. And we're going to see this in future videos. And so if you are actually trying to construct a confidence interval for a sample mean, and you don't know the true standard deviation of your population, which is normally the case, instead of doing this, what we're going to do is, we're gonna take our sample mean, plus or minus, and our critical value, we'll call that t star, times our sample standard deviation, which we can calculate, divided by the square root of n. And so the real functional difference is that this actually is going to give us the confidence interval that actually has the level of confidence that we want.