Which hypothesis suggests no effect or relationship?

The null hypothesis is a fundamental concept in hypothesis testing and statistics. It specifically posits that there is no effect or relationship between the variables being studied. This means that any observed differences or associations in the data are due to random chance rather than a true underlying connection.

In research, the null hypothesis serves as a baseline or default position that researchers aim to test against. When conducting an experiment or analyzing data, researchers typically gather evidence to either reject or fail to reject the null hypothesis based on statistical analysis. If sufficient evidence is found, the null hypothesis may be rejected in favor of the alternative hypothesis, which proposes that there is indeed an effect or relationship.

The alternative hypothesis, research hypothesis, and confounding hypothesis serve different roles in research and do not specifically assert that there is no effect or relationship. The alternative hypothesis suggests that there is an effect or a difference; the research hypothesis is often synonymous with the alternative hypothesis. Meanwhile, a confounding hypothesis relates to potential external variables that could influence the outcomes of the study. Thus, the null hypothesis distinctly captures the idea of asserting no effect or relationship between the variables.