If a one-sided null hypothesis for a single mean cannot be rejected at a given significance level, then the corresponding two-sided null hypothesis (i. e., the same sample size, the same standard deviation, and the same mean) will be rejected at the same significance level.

Two-sided null hypothesis (i.e., the same sample size, the same standard deviation, and the same mean) will also be rejected at the same significance level.

Step-by-step explanation:

The decision rule to reject a null hypothesis at α% level of significance is, if the p-value of the test is less than the level of significance then the null hypothesis of the test is rejected. And if p-value of the test is more than the level of significance then the null hypothesis of the test is failed to be rejected.

Now for a two-tailed test the p-value is, , i.e. the p-value is decreased for a two tail test.

If a null hypothesis of a one-sided test is rejected at a significance level α, then it would mean that the p-value < α.

As the p-value < α then the two-tailed p-value is definitely less than α.

So the two-tail null hypothesis will also be rejected at the same level of significance.

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step-by-step explanation: