Numerical Variables
Numerical variables are quantitative variables that represent numerical values. In data science, numerical variables are used to measure and analyze numerical data. These variables can be further classified into two types: discrete and continuous. Discrete numerical variables are those that can only take on specific values, such as integers, while continuous numerical variables can take on any value within a range. Numerical variables are important in data science because they allow for statistical analysis and modeling, such as regression analysis and hypothesis testing. They are also used in machine learning algorithms, such as decision trees and neural networks, to make predictions and classifications based on numerical data.
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