Because if your null hypothesis is true, let's say that your significance level is 5%. Well, 5% of the time, even if your null hypothesis is true, you're going to get a statistic that's going to make you reject the null hypothesis. So one way to think about the probability of a type one error is your significance level. Now, if your null hypothesis is true and you fail to reject it, well, that's good. This, we could write this as, this is a correct, correct conclusion. The good thing just happened to happen this time. Now, if your null hypothesis is false and you reject it, that's also good.