# If you are already certain that a null hypothesis is false, then: Significance testing provides

If you are already certain that a null hypothesis is false, then:
Significance testing provides no useful information since all it does is reject a null hypothesis.
Significance testing is informative because you still need to know whether an effect is significant even if you know the null hypothesis is false.
When a difference is significant you can draw a confident conclusion about the direction of the effect.
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Null hypothesis of the test is the nullified statement about the population parameter. Whereas, the alternative hypothesis is the alternative statement of the null hypothesis. When the null hypothesis of the test is rejected, it means that the effect of the test is significant.
If already known that the null hypothesis is false, Significance testing is informative because you still need to know whether an effect is significant even if you know the null hypothesis is false.