📘 Chapter 12: Multiple Linear Regression

🎮 Interactive Apps (HTML/JS)

• 12.1.1 – Multiple Linear Regression Intro
• 12.1.2 – Least Squares Estimation
• 12.1.3 – Matrix Formulation
• 12.2 – Hypothesis Tests in Multiple Regression
• 12.3 – Confidence Intervals & 12.4 – Model Utility
• 12.5 – Model Adequacy Checking (Residual, Leverage, Cook)
• 12.6 – Aspects of Multiple Regression Modeling (VIF, Dummy, Cp, Adj R²)

📽️ PPT Slides

• Download Chapter 12 Slides (ch12.pptx)

📝 Quiz

Coming soon! Quiz on multivariate slope testing, confidence intervals, VIF, Cp, and regression diagnostics.

📚 Homework

Coming soon! Full solution sets for Chapter 12 MLR problems and student GPA case studies.

💬 Excel

• Chapter 12 - Excel for Multiple Linear Regression (MLR), VIF, Cook’s Distance, and Adjusted R²

📢 Student Q&A

• Q: How do I interpret a coefficient in MLR?
  A: It shows the expected change in Y for a 1-unit increase in that X, holding other Xs constant.
• Q: What if VIF is high?
  A: It suggests multicollinearity. Consider removing or combining variables.
• Q: How do I spot an influential point?
  A: Use Cook’s Distance. If Dᵢ > 1, investigate the data point.
• Q: What is the difference between R² and Adjusted R²?
  A: Adjusted R² penalizes for adding variables and helps prevent overfitting.
• Q: When to use dummy variables?
  A: When including categorical inputs like gender, major, or region.
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