If you actually then said, oh, this is a binomial distribution, so the probability that our random variable equals some given value k, the probability that exactly three cars pass in a given hour, it would then be equal to n. So n would be 60. Choose k, and three cars, times the probability of success, so the probability that a car passes in any minute, so it would be lambda over 60 to the number of successes we need, so to the kth power, times the probability of no success, or that no cars pass, to the n minus k. If we have k successes, we have to have 60 minus k failures. There are 60 minus k minutes where no car passed. And this actually wouldn't be that bad of an approximation, where you have 60 intervals and you say this is a binomial distribution, and you'd probably get reasonable results. But there's a core issue here. In this model, where we model it as a binomial distribution, what happens if more than one car passes in an hour? Or more than one car passes in a minute?