Well, if you succeeded in trial one, that means that there's now only 10 female names in the hat out of 19, and if you don't have success in trial one, then you will have, then it'll be 11 out of 19, so your probability does change based on previous outcomes, and so the trials are not independent, and so x is not a binomial variable. So this one is true. The trials are not independent, so that violates that condition for being a binomial variable. In order to be a binomial variable, all your trials have to be independent of each other, and so we'd rule this last one out because this last one says that x has a binomial distribution, or it is or does meet all the conditions for being a binomial variable. Let's do another example. So here we have different scenarios, and I have the conditions for binomial variable written right over here, and so once again, pause the video and look at each of these scenarios for random variables, and look at these conditions, and think about whether these random variables are binomial or not. So let's look at the first one.