What does a probability distribution describe?

A probability distribution specifically describes the likelihood of obtaining the possible values of a random variable. This concept is fundamental in statistics and probability theory, as it provides a comprehensive framework for understanding how outcomes are dispersed over a range of values.

For example, in a discrete probability distribution, each possible value that a random variable can take has an associated probability, indicating how likely that value is to occur. In continuous distributions, the focus is on intervals and densities instead of specific probabilities for exact values. Therefore, understanding probability distributions allows for better predictions and insights regarding random phenomena and variable behaviors.

The other choices, while related to data and statistics, do not accurately capture the essence of what a probability distribution is. The total number of events in a sample space merely defines the context but doesn't reflect the likelihood of specific outcomes. The mean of a dataset is a single summary statistic and does not involve the range of probabilities across possible values. Similarly, frequency refers to how often certain outcomes occur but does not express the probabilities tied to those outcomes in the probabilistic sense that a distribution does.