A Type I error occurs when a true null hypothesis is incorrectly rejected (false positive). A Type II error happens when a false null hypothesis isn't rejected (false negative). The former implies acting on a false alarm, while the latter means missing a genuine effect. Both errors have significant implications in research and decision-making.

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