How does multiple linear regression differ from simple linear regression?
- Multiple linear regression cannot handle categorical variables, simple linear regression can
- Multiple linear regression is not suitable for prediction tasks
- Multiple linear regression requires a larger dataset
- Multiple linear regression uses multiple independent variables, simple linear regression only uses one
The main difference between simple and multiple linear regression is the number of independent variables. While simple linear regression uses only one independent variable to predict the dependent variable, multiple linear regression uses two or more independent variables to predict the dependent variable.
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