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.
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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.