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Multiple Linear Regression

  1. Extending to multiple predictor variables
  2. Feature selection and engineering
  3. MicroSim: Multi-dimensional regression explorer
  4. Handling categorical variables
  5. Interaction effects and polynomial terms
  6. Multicollinearity detection and treatment
  7. Model interpretation in multiple dimensions