When Linear Regression Assumptions Are Violated: The Bridge Engineer Who Ignored the Cracks and Declared It Safe

Your R² is 0.92. Your p-values are significant. Your model looks perfect. But you violated the assumptions. It's like an engineer who measured a bridge's paint quality (perfect!) while ignoring structural cracks. Here's exactly what goes wrong with each violation — and why "good metrics" can hide catastrophic problems.