# 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.

## Discrete vs. continuous random variables, visualized

## Learning resources

Khan Academy: Discrete and continuous random variables

#### Carsten Grube

Freelance Data Analyst

##### Normal distribution

##### Two-sample inference

##### Confidence intervals

##### Simple linear regression, fundamentals

##### ANOVA & the F-distribution

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