Esra

Read the effect size and its interval first. If the interval is wide, significance is not rescuing anything.

The thing to look for instead, and the reason people who work with this stopped leading with significance: the effect size and the confidence interval.

The effect size is how big the difference actually is, in units you can think about. Three minutes. Two percentage points. Half a mark. That is the number that tells you whether it matters.

The confidence interval is the range of values consistent with the data. It carries the significance information: if the interval excludes no difference at all, the result is significant: and it also tells you how precise the estimate is, which significance alone hides completely.

This is why an interval is more informative than a verdict. A result reported as significant might be an interval from a huge effect to a tiny one, and that is a completely different thing from a narrow interval around a modest effect, even though both get the same word.

A practical reading habit: when you meet a significant result, look for the size. If the article does not give it, that is itself informative: a genuinely large effect is nearly always reported as a number, because it is the impressive part.

And if you only remember one thing: significant is a statement about how surprising the data is, not about how big or how important the finding is.