When the probability of a Type I error increases, the probability of a Type II error must decrease, ceteris paribus.

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Quizplus · Accepted Answer

A Type I error occurs when a true null hypothesis is incorrectly rejected, while a Type II error happens when a false null hypothesis is not rejected. Increasing the probability of a Type I error (by raising the significance level, for example) makes the test more likely to reject the null hypothesis, thereby reducing the probability of failing to reject a false null hypothesis (Type II error), assuming all other factors remain constant.

When the Probability of a Type I Error Increases, the Probability