When testing a hypothesis, an acceptable significance level such as 0.05 or 0.01 is typically used. This significance level corresponds to the probability of making a type I error — that is, incorrectly rejecting a null hypothesis. However, when several statistical tests are being performed simultaneously, using the same error rate for the set of all comparisons can increase the probability of making type I errors. Using the adjustment method parameter in Dataiku DSS can avoid this situation.