In statistical hypothesis testing, the null hypothesis (H0) formally describes some aspect of the statistical behaviour of a set of data; this description is treated as valid unless the actual behaviour of the data contradicts this assumption. Thus, the null hypothesis is contrasted against another hypothesis. Statistical hypothesis testing is used to make a decision about whether the data contradicts the null hypothesis: this is called significance testing. A null hypothesis is never proven by such methods, as the absence of evidence against the null hypothesis does not establish it. In other words, one may either reject, or not reject the null hypothesis; one cannot accept it. Failing to reject it gives no strong reason to make decisions based on its truth, but it also allows for the possibility of obtaining further data and then re-examining the same hypothesis.