statistical significance

In summary, all a test of statistical significance means is that if the null hypothesis (often no difference) is true, then the probability of seeing the measured results is low (e.g., < 5%, or < 1%). This is then used as evidence against the null hypothesis. It is good to remind ourselves of this occasionally, but for most purposes an informal understanding is that statistical significance is evidence for the alternative hypothesis (often what you are trying to show), but may be wrong—and the smaller the % or probability, the more reliable the result. However, all that non-significance tells you is that you have neither proved nor disproved your hypothesis.