What does statistical significance indicate in experimental research?

Statistical significance is a crucial concept in experimental research as it helps researchers determine whether the observed effects of a treatment or intervention are likely to reflect a true difference between groups rather than being the result of random variation. When results are deemed statistically significant, it typically suggests that the probability of observing such differences due to chance is very low, often below a predefined threshold such as 0.05.

In this context, stating that a true difference between groups exists is essential because it means that the effects observed in the study are not merely due to random fluctuations in the data. Rather, they indicate a consistent and dependable effect of the treatment or intervention being studied. Therefore, statistical significance supports the conclusion that the treatment has likely produced a real change, enabling researchers and practitioners to interpret the findings with greater confidence.

While a statistically significant result does suggest a genuine difference, it does not inherently imply clinical effectiveness or the size of the difference, nor does it claim that results are free from chance in absolute terms; it simply asserts that the chances of the observed effect occurring randomly are negligible.