Once again, many times you'll just be told to assume that that has been met because it might, at least in an introductory statistics class, be a little bit hard to figure this out on your own. Now the next condition is related to that, and this is the idea of having equal variance, equal variance, and that's just saying that each of these normal distributions should have the same spread for a given x. And so you could say equal variance, or you could even think about them having the equal standard deviation. So for example, if for a given x, let's say for this x, all of a sudden you had a much lower variance, maybe it looked like this, then you would no longer meet your conditions for inference. Last but not least, and this is one we've seen many times, this is the random condition. And this is that the data comes from a well-designed random sample or some type of randomized experiment. And this condition we have seen in every type of condition for inference that we have looked at so far.