Which type of distribution demonstrates the probability of outcomes for a random variable?

The choice of probability distribution is accurate because it specifically represents the probabilities of different possible outcomes for a random variable. A probability distribution assigns a probability to each possible value of the variable, effectively quantifying the likelihood of each outcome occurring. This is essential in statistics and data science as it provides a framework for making inferences and predictions based on random processes.

Statistical distribution is a broader term that encompasses various ways of illustrating how values are spread or clustered but doesn’t directly imply the probability aspects. Frequency distribution refers to how often each value occurs in a dataset, focusing more on counts than on probabilities. The normal distribution is a specific type of probability distribution that depicts the bell-shaped curve often associated with real-valued random variables, but it is just one example of many types of probability distributions. Thus, while all distributions serve to illustrate data, the term probability distribution specifically emphasizes the relationship between outcomes and their associated probabilities.