The null hypothesis (H0) is a fundamental statement in statistical hypothesis testing. It postulates that there is no effect, no association, or no difference between the groups under investigation. In a typical clinical trial, the null hypothesis might, for example, be: “There is no difference in efficacy between the new investigational medicinal product and placebo.”
The entire statistical testing procedure is designed to gather evidence against the null hypothesis. Researchers aim to refute the null hypothesis (to “reject” it). If the data obtained from the study are so unlikely that, assuming the null hypothesis is true, they would occur only rarely (typically with a probability of less than 5%, the p-value), the null hypothesis is rejected. This leads to acceptance of the alternative hypothesis (H1), which states that an effect does in fact exist. The precise formulation of H0 is a crucial first step for biostatisticians at a CRO when planning the statistical analysis.