What is an example of a hypergeometric probability distribution?

The hypergeometric probability distribution is specifically used to model scenarios where samples are drawn from a finite population without replacement. This means that each draw affects the probabilities of subsequent draws because the total number of potential outcomes decreases with each selection.

In contrast to other distributions, such as the binomial distribution, which assumes independent trials with replacement, the hypergeometric distribution explicitly accounts for the changing nature of the population as items are selected. This makes option B the correct choice, as it accurately describes the key characteristic of the hypergeometric distribution's sampling method.

The other options touch upon different concepts; for example, distributions that show probabilities for averages are typically linked to normal distributions or similar. A focus on a single population does not capture the essential no-replacement aspect that defines the hypergeometric distribution, and a distribution used for independent trials refers to the binomial distribution, which deals with replacement and does not apply here. Thus, the essence of option B aligns perfectly with the defining features of the hypergeometric distribution.