Simple regression fits a line; add a second variable and you're fitting a plane. Seeing that lift off the page made coefficients click for me. The coefficient everyone misreads: it's the effect of one variable with the others held constant, not in isolation. Overfitting trap: your fit score climbs even when you add pure noise. R² going up is not evidence your model got better. Multicollinearity trap: when two predictors move together, the model can't tell which one is actually doing the work, and the coefficients get unstable. submitted by /u/Away-Excitement-5997 [link] [comments]