Well, we figured that out. If it really was accurate 99% of the time, then the probability of getting this outcome is only 0.3%. So if you assume true, if you assume hypothesis, I'll just write hype. If you assume the hypothesis is true, the probability of the outcome you got, probability of observed outcome is approximately 0.3%. And so you say, look, you know, maybe it's definitely possible that I just got very, very, very, very unlikely, but based on this, I probably should reject my hypothesis because the probability of me getting this outcome, if the hypothesis was true, is very, very, very, very low. And as we go deeper into statistics, you'll see that there are thresholds that people often set for, you know, if the probability of something happening or not happening is above or below some threshold, then we might reject a certain hypothesis. But in this world, you could see that, look, if my test really was accurate 99% of the time, for me to get, when I apply it to 100 people, it's only accurate 95 out of 100.