What are some common methods to handle Multicollinearity in a dataset?
- All of these methods can be used.
- Increasing the sample size
- Performing Principal Component Analysis
- Removing highly correlated variables
All the mentioned methods can be used to handle Multicollinearity. Depending on the severity of the multicollinearity and the specific context, you might choose to remove highly correlated variables, increase your sample size, or perform Principal Component Analysis (PCA) to create a smaller set of uncorrelated variables.
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