If both Type 1 and Type 2 errors are costly, set the level of significance very low and increase the sample size.

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Quizplus · Accepted Answer

Setting the level of significance very low (e.g. decreasing it from 0.05 to 0.01) reduces the probability of making a Type 1 error (rejecting a true null hypothesis) but increases the probability of making a Type 2 error (failing to reject a false null hypothesis). Increasing the sample size can help reduce the probability of Type 2 errors by increasing the power of the statistical test, which is the probability of rejecting a false null hypothesis. Thus, by balancing the trade-off between Type 1 and Type 2 errors, both of which can be costly in different ways, researchers can optimize the design and analysis of their studies.

If Both Type 1 and Type 2 Errors Are Costly