Let's look at a population where the probability of success, and we'll define success as 1, as having a probability of p. And the probability of failure is 1 minus p, whatever this might be. And obviously, if you add these two up, if you view them as percentages, these are going to add up to 100%. Or if you add up these two values, you're going to add to 1. And that needs to be the case, because these are the only two possibilities that can occur. If this is 60% chance of success, there has to be a 40% chance of failure. 70% chance of success, 30% chance of failure. Now, with this definition of this, and this is the most general definition of a Bernoulli distribution, it's really exactly what we did in the last video.