What is a null hypothesis (H0)?

A null hypothesis (H0) serves as a foundation for statistical testing, typically positing that there is no effect or difference in the population being studied. It acts as a default or baseline assumption that any observed differences or effects in the data are due to random chance rather than any real underlying phenomenon.

When conducting hypothesis testing, researchers seek to either reject the null hypothesis in favor of an alternative hypothesis, which proposes that there is a specific effect or difference, or fail to reject the null hypothesis, which suggests that there is insufficient evidence to support the alternative. The null hypothesis is essential for determining statistical significance and helps establish a standardized framework for evaluating research findings.

In contrast, other options misrepresent the nature of the null hypothesis. For instance, the assertion that it assumes an effect exists in the population is incorrect, as it is fundamentally skeptical of the existence of such effects until there is substantial evidence to support them. The claim that it serves as a method for testing reliability does not capture its primary function in hypothesis testing. Lastly, suggesting it is a claim about sampling error does not accurately reflect the null hypothesis’s role in defining the absence of effects or differences.