Evidence-appraisal glossary
Null hypothesis
The null hypothesis is the default claim that there is no real effect or no difference, for example that a treatment works no better than placebo. Statistical tests assess how well the data fit this assumption; a small p-value gives reason to doubt it.
Also called: H0, H-null.
The null hypothesis (written H0) is the starting assumption a study tries to disprove. It typically states that any observed difference is zero: the drug and placebo have the same effect, or two groups have equal average outcomes. Statistical testing works by asking how likely the observed data would be if the null hypothesis were true, then judging whether that likelihood is low enough to reject it in favor of an alternative. Rejecting the null is not the same as proving the alternative with certainty, and failing to reject it is not proof of no effect; it may just mean the study lacked power to detect one. When reading a study, identify exactly what the null hypothesis claims, since a poorly chosen null can make a test misleading. For example, a trial comparing a new painkiller to placebo sets the null as no difference in pain relief, and a low p-value indicates the data are hard to square with that no-difference assumption.
This is a plain-language methodology definition for reading research. It is general education, not medical advice.