Navigating Model Selection & Regularization: A Journey through R

The session is designed for virtual attendees seeking a practical and conceptual understanding of statistical modeling. Participants will explore key techniques for model selection, including AIC, BIC, and cross-validation, alongside regularization methods like LASSO, Ridge, and Elastic Net. Through intuitive explanations and hands-on demonstrations in R, the session emphasizes balancing model accuracy, complexity, and interpretability. Whether you're refining predictive models or ensuring robust inference, this guided tour will enhance your ability to build reliable models and make data-driven decisions using the powerful tools within R.