This
session increases complexity in a controlled way: we replace simple correlations with VIF, retain conditional subset variables (including a negative Bedroom coefficient), and use ZIP codes to capture economic diversity within a single resort town. The post-outlier model reaches practical BLUE
status.
What We Cover in Session 3:
1. Beyond Pairwise Pearson (r): Why two-variable correlation matrices
fail to catch joint multicollinearity—and how to implement Variance
Inflation Factor (VIF) auxiliary regressions to certify feature schema
stability (< 5.0 threshold).
2. Hierarchical Variable Architecture: How to model conditional subset
variables (Bedrooms, Bathrooms, and Pool) against foundational spatial/physical
anchors, including economic rationale for negative bedroom coefficients in
open-layout resort markets.
3. Micro-Spatial Vectoring: Simulating intra-town economic diversity
using k-1 ZIP code dummy structures.
4. The Power of Two-Pass Z-Score Purging: How trimming just 5.12% of extreme
residual noise (|Z|> 2.0) transforms model efficiency and elevates the
specification to certified BLUE status.
Read
Session 3 on Substack:
https://sidsom.substack.com/p/session-3-model-building-at-the-intermediate
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