A conditional distribution describes the probability distribution of a random variable given that another variable takes on a specific value. It helps to understand how one variable behaves when we know the state of another. For example, in a dataset involving height and weight, the conditional distribution of weight given a specific height shows how weight varies for individuals of that height. This concept is essential in statistics and data analysis, as it allows researchers to make informed predictions and decisions based on known conditions. By analyzing conditional distributions, one can uncover relationships and dependencies between variables, enhancing the understanding of complex data sets.