We have to say, what we're going to do is, we're going to assume that our null hypothesis is correct. And then given, with that assumption that the null hypothesis is correct, we're going to see what is the probability of getting this sample data right over here. And if that probability is below some threshold, we will reject the null hypothesis in favor of the alternative hypothesis. Now, that probability threshold, and we've seen this before, is called the significance level, sometimes called alpha. And here, we're going to decide for a significance level of 95%. Or another way to think about it, we want there to be, assuming that the null hypothesis is correct, we want there to be no more than a 5% chance of getting this result here, or no more than a 5% chance of incorrectly rejecting the null hypothesis when it is actually true, or that would be a type 1 error. So if there's less than a 5% probability of this happening, we're going to reject the null hypothesis.