And so based on your confidence level you wanna have, let's say it's 95%, based on the degrees of freedom, which we'll see will come out of how many data points we have, we can figure this out. And from our sample, we can figure this out, and we can figure this out, and then we would have constructed a confidence interval. We'll also see that you could do hypothesis testing here. You could say, hey, let's set up a null hypothesis, and the null hypothesis is going to be that there's no non-zero linear relationship, or that the true population slope of the regression line, or slope of the population regression line, is equal to zero, and that the alternative hypothesis is that the true relationship could either be greater than zero, it's a positive linear relationship, or that it's just non-zero. And then what you could do is, assuming this, you could see what's the probability of getting a statistic that is at least this extreme, or more extreme. And if that's below some threshold, you might reject the null hypothesis, which would suggest the alternative. So this and this are things that we have done before, where you're creating a confidence interval around a statistic, or you're doing hypothesis testing, making assumptions about a true parameter.