Discrete Variables
In data science, discrete variables are variables that can only take on a finite or countably infinite set of values. These values are typically integers or whole numbers, and they are distinct and separate from one another. Discrete variables are often used in statistical analysis to represent categorical data, such as gender, race, or occupation. They can also be used to represent numerical data that has been rounded or truncated to a specific set of values. Discrete variables are important in machine learning algorithms, where they are used to represent features or attributes of a dataset. They are often used in decision trees, where they are used to split the data into different branches based on the value of the variable. Other common applications of discrete variables include probability distributions, hypothesis testing, and regression analysis.
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