Directional (one-tailed) tests are used when researchers...

Directional (one-tailed) tests are used when researchers...

• A. Are testing for any difference between groups without specifying direction.
• B. Make a claim about the direction of the effect.
• C. Estimate the size of the treatment effect.
• D. Assess the probability of Type II error.

Answer: (B)

When researchers have a specific prediction about the direction of an effect, a directional (one-tailed) test is used to test that exact expectation. By concentrating the rejection region in the predicted direction, this approach increases the chance of detecting an effect if the prediction is correct. For example, if you expect a treatment to increase an outcome, you test whether the mean is larger than the baseline rather than testing for any difference in either direction. If the data show the effect in the opposite direction, a one-tailed test won’t provide evidence for the effect in that direction because all the significance is in one tail. This method is chosen only when there is a solid directional hypothesis; otherwise, a two-tailed test is more appropriate to detect effects in both directions. It’s not primarily about estimating how big the effect is or about the probability of Type II error.

When researchers have a specific prediction about the direction of an effect, a directional (one-tailed) test is used to test that exact expectation. By concentrating the rejection region in the predicted direction, this approach increases the chance of detecting an effect if the prediction is correct. For example, if you expect a treatment to increase an outcome, you test whether the mean is larger than the baseline rather than testing for any difference in either direction. If the data show the effect in the opposite direction, a one-tailed test won’t provide evidence for the effect in that direction because all the significance is in one tail. This method is chosen only when there is a solid directional hypothesis; otherwise, a two-tailed test is more appropriate to detect effects in both directions. It’s not primarily about estimating how big the effect is or about the probability of Type II error.