Diagnose and fix multicollinearity in income regression

You want to estimate the relationship between **gender** and **income** using a regression model, while controlling for other covariates such as: - `age` - `education` (e.g., degree level or years of schooling) - `years_since_degree` Questions: 1. What is multicollinearity, and is it likely to be present among these predictors? Why? 2. How would you diagnose multicollinearity in practice (specific checks/metrics)? 3. If multicollinearity exists, what are practical ways to address it while still answering the question about gender and income? Discuss tradeoffs (interpretability vs prediction).