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A fitted model is a hypothesis with numbers attached; the diagnostics decide whether the numbers mean anything.
Least squares will return coefficients for almost any data set you hand it, which is exactly why the fit itself proves so little. Residual structure, influential points and collinearity each tell you whether the estimate is stable enough to act on.
