Type I errors are usually considered more "costly" although this can lead to conservative decision making.

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Type I errors, also known as false positives, occur when a hypothesis is rejected even though it is actually true. This can lead to incorrect decisions and potentially costly consequences. As a result, many decision-makers try to minimize the probability of Type I errors by setting a high significance level or adopting a conservative approach, which may lead to fewer false positives but also to missing important opportunities or trends.

Type I Errors Are Usually Considered More "Costly" Although This