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Multiple Linear Regression

via Codecademy


Learn how to build and interpret linear regression models with more than one predictor variable.
This course builds on simple linear regression by working with multiple predictor variables rather than just one. Multiple linear regression is a powerful tool for data scientists looking to analyze how multiple factors are related to an outcome. Python is used by professionals in the Data Analysis and Data Science fields as part of their daily work.

### Take-Away Skills
In this course, you will learn how to make a multiple linear regression model, with more than one predictor variable in Python. In addition to learning how to make the model, you will also learn how to interpret it. This is almost more critical than making the model itself — being able to communicate the findings that you get from your model is an essential skill of a data scientist.


  • Multiple Linear Regression: Leverage the power of multiple variables to build predictive algorithms!
    • Lesson: Multiple Linear Regression
    • Article: Matrix Representation of Linear Regression
    • Lesson: Interactions and Polynomial Terms
    • Article: Log Transformations (And More)
    • Quiz: Multiple Linear Regression
    • Project: Algerian Forest Fires
    • Article: Next Steps


4.6 rating at Codecademy based on 9 ratings

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