<span>The concept goes to the idea of falsification. The null hypothesis is based on the concept that there is no statistically significant difference between the two factors being studied. The outcome, when it is measured, seeks to falsify this statement: if it does not, then it simply does not falsify the null hypothesis. However, it does not mean that the null hypothesis is accepted as correct: it may simply mean that there are other, unstudied factors at play that were not tested and could have some sort of effect.</span>
