Your linear model won’t sing if its backstage chaos goes unchecked. This guide dives into the five bedrock assumptions—linearity, normality, homoscedasticity, no autocorrelation, and little multicollinearity. Learn how each assumption can break your estimates, spot trouble with scatter, Q‑Q, DW, and BP tests, then patch the leaks with transforms, robust errors, WLS, or time‑series tricks. Walk away knowing when to trust the p‑values and when to call in GAMs, GLS, or bootstrap