Aug 6, 2025
Ridge vs. OLS: Overcoming Multicollinearity Issues
Let’s talk about something that might be silently sabotaging your regression models: multicollinearity. Imagine you’re baking a cake, and two of your ingredients—say, sugar and honey—are both sweeteners. Individually great, but too much of both? The balance gets thrown off. That’s what happens when your model has too many similar (highly correlated) predictors. The estimates go haywire. Enter:…