Confounding is crucial to identify because it can lead to incorrect conclusions about the relationship between the exposure and the outcome. For example, if we are studying the effect of a new drug on heart disease, a confounder like smoking—which is related both to drug use and heart disease—could give a misleading impression of the drug's effectiveness.
