Correlation-Based Variable Selection

Correlation-Based Variable Selection

Read It: Correlation-Based Variable Selection

One way to selet the optimal variables for multiple linear regression is through a correlation analysis. By determining which explanatory variables are most highly correlated with the response, you can get a better idea of important variables, thus implement models with higher adjusted R² values. Below, we demonstrate how to implement this process in Python.

 Watch It: Video -  Correlation Variable Selection (10:13 minutes)

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Using the pre-coded variables below. Calculate and print the correlation matrix. Are any of the variables highly correlated? Which would you include in your multiple linear regression model? 

• script.py
• solution.py
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import pandas as pd

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