Type II errors are typically greater for two-tailed hypothesis tests than for one-tailed tests.

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A Type II error occurs when the null hypothesis is not rejected when it is false. In a two-tailed test, the rejection region is split between the two tails of the distribution, making it harder to reject the null hypothesis for a given significance level compared to a one-tailed test where all the rejection region is on one side. This means that, all else being equal, a two-tailed test is more conservative and has a higher chance of a Type II error than a one-tailed test.

Type II Errors Are Typically Greater for Two-Tailed Hypothesis Tests