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# Discrete vs. continuous random variables

Here, in Discrete vs. continuous random variables, we will look at the two types of random variables: Discrete and continuous and see how to understand and distinguish between them. In probability and statistics, a random variable is typically referred to as a variable from a population or a sample.

## Discrete variables

Discrete variables can take on distinct values. They are countable, like:

• number of staffs in one department,
• number of visits to a web page,
• price for a green pepper,
• number of visitors at a football match,
• results of rolling a die or flipping a coin

Discrete variables can be success or failure in an experiment, like “yes” or “no” and other countable data that cannot be granulated as opposed to continuous variables:

## Continuous variables

Continuous values can take on any value in a range and can even be infinite. They are quantities that have “endless continuity”, or that you cannot say “the number of”.

For example, the value of some bond or the height of persons. Continuous variables cannot be measured as fixed numbers, and they are typically:

• mass
• height
• weight
• temperature
• pressure
• volume
• density
• distance

## Random variable in statistics

Whether data is discrete or continuous variables is part of what determines what probability distributions and procedures they follow.

## Learning resources

Khan Academy: Discrete and continuous random variables

#### Carsten Grube

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##### ANOVA & the F-distribution

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