In a hypothesis test, a type II error occurs when you fail to reject a null hypothesis that is actually false. In other words, you obtain an insignificant test result even though a population effect actually exists. Some combination of a small sample size, inherent variability in the data, and bad luck with random sample error might have obscured the population effect. You can decrease the probability of a type II error by increasing the power of the test.
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