In a one-sided test, if p < α, what does this indicate?

In a one-sided test, if p < α, what does this indicate?

• A. Reject the null in the opposite direction.
• B. Fail to reject the null.
• C. Reject the null in favor of the specified direction.
• D. Conclude a large effect.

Answer: (C)

In a one-sided test, the p-value reflects the probability, under the null hypothesis, of observing data as extreme as ours in the specified direction of the alternative. If that p-value is smaller than the significance level α, the observed result is unlikely under the null in that direction, so you reject the null in favor of the direction you specified. This is why the correct interpretation is that there is evidence supporting the null being rejected toward the specified direction. It’s not about rejecting in the opposite direction, which would require looking at the opposite tail. It’s not a default to fail to reject when p < α, and a small p-value doesn’t quantify how large the effect is, only that there is statistically significant evidence in that direction.

In a one-sided test, the p-value reflects the probability, under the null hypothesis, of observing data as extreme as ours in the specified direction of the alternative. If that p-value is smaller than the significance level α, the observed result is unlikely under the null in that direction, so you reject the null in favor of the direction you specified. This is why the correct interpretation is that there is evidence supporting the null being rejected toward the specified direction. It’s not about rejecting in the opposite direction, which would require looking at the opposite tail. It’s not a default to fail to reject when p < α, and a small p-value doesn’t quantify how large the effect is, only that there is statistically significant evidence in that direction.