Holding other factors constant, it is harder to reject the null hypothesis for a mean when conducting a two-tailed test rather than a one-tailed test.

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In a two-tailed test, the null hypothesis is rejected when the test statistic falls in either the upper or lower tail of the distribution, which increases the probability of a type II error (i.e., failing to reject a false null hypothesis). This makes it harder to reject the null hypothesis than in a one-tailed test, where the rejection region is only on one side of the distribution.

Holding Other Factors Constant, It Is Harder to Reject the Null