Probability distributions are statistical functions that describe the likelihood of obtaining possible values that a random variable can take. In other words, the values of the variable vary based on the underlying probability distribution.
Suppose you draw a random sample and measure the heights of the subjects. As you measure heights, you create a distribution of heights. This type of distribution is useful when you need to know which outcomes are most likely, the spread of potential values, and the likelihood of different results.
Discrete probability functions are also known as probability mass functions and can assume a discrete number of values. For example, coin tosses and counts of events are discrete functions. These are discrete distributions because there are no in-between values. For example, you can have only heads or tails in a coin toss. Similarly, if you’re counting the number of books that a library checks out per hour, you can count 21 or 22 books, but nothing in between.