In statistics, a null hypothesis (H₀) is a hypothesis (scenario) set up to be nullified, refuted, or rejected ('disproved' statistically) in order to support an alternative hypothesis. When used, the null hypothesis is presumed true until statistical evidence, in the form of a hypothesis test, indicates otherwise — that is, when the researcher has a certain degree of confidence, usually 95% to 99%, that the data does not support the null hypothesis. It is possible for an experiment to fail to reject the null hypothesis. It is also possible that both the null hypothesis and the alternate hypothesis are rejected if there are more than those two possibilities.

In scientific and medical applications, the null hypothesis plays a major role in testing the significance of differences in treatment and control groups. The assumption at the outset of the experiment is that no difference exists between the two groups (for the variable being compared): this is the null hypothesis in this instance. Other types of null hypotheses may be, for example, that:

• values in samples from a given population can be modelled using a certain family of
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