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Data & Analytics · Advanced

Multicollinearity

High correlation among predictor variables in a regression, which makes coefficient estimates unstable and hard to interpret.

Definition

Multicollinearity is detected with correlation matrices or the variance inflation factor (VIF > 5-10). Remedies include removing or combining predictors, PCA or regularization. Predictions may remain accurate even when coefficients are unreliable.

Exam tip

High VIF = multicollinearity, which hurts interpretability more than prediction.

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