# Discrete Variable

## Definition of Discrete Variable

A discrete variable is a variable that can only take on certain, specific values. Contrast this with a continuous variable, which can take on any value within a given range. Discrete variables are often used in statistical models to represent outcomes that can only happen a certain number of times, or that happen in a specific order.

## What is a Discrete Variable used for?

A Discrete Variable is a type of data that can take on only certain pre-defined values, as opposed to a continuous variable which can take on any value within a range. It is often used in data science and machine learning to represent categorical data, such as a person’s gender or profession.

Discrete Variables are beneficial for a number of reasons. For example, they enable machine learning algorithms to quickly classify data into various categories and draw meaningful conclusions from it. Additionally, discrete variables enable researchers to group similar observations together and analyze them collectively, which can lead to more accurate predictions and insights.

Discrete variables also allow for more efficient storage and retrieval of data. By reducing the size of large datasets into manageable chunks of information with discrete values, the processing time needed to process the information is reduced significantly. This makes it easier for machines to learn from and process complex datasets quickly and accurately.

Moreover, working with discrete variables also allows machines to work with more specific parameters than would be possible with continuous variables. For instance, when dealing with images or audio recordings, discrete values help identify distinct features within an observation that may be important for analysis and classification purposes.