AIC & BIC: Model Comparison Criteria
AIC (Akaike) and BIC (Bayesian) Information Criteria measure model quality, penalizing for complexity to prevent overfitting.
- Lower AIC/BIC → better model
- AIC = n·ln(RSS/n) + 2k BIC = n·ln(RSS/n) + k·ln(n)
- BIC penalizes extra parameters more than AIC
- BIC tends to select simpler models
Try it in the app
Try: Add an X variable → re-run regression → compare new AIC to old AIC below the table. Decrease means the variable improves the model.