Nonnegative Versus Unrestricted One important special case of bounded distributions is when the only possible values are nonnegative. For example, if you want to model the random cost of manufacturing a new product, you know that this cost must be nonnegative. There are many other such examples. In these cases, you should model the randomness with a probability distribution that is bounded below by 0. This prevents negative values that make no practical sense.