What is the opposite of a hypothesis, indicating no effect or difference?

The term that describes the opposite of a hypothesis, indicating no effect or difference, is indeed the null hypothesis. A null hypothesis serves as a foundational concept in statistical hypothesis testing, providing a baseline that suggests that any observed differences in data are due to chance rather than a specific effect or intervention.

When researchers formulate a study, they typically propose a hypothesis, which is a statement suggesting a potential effect or relationship. The null hypothesis, on the other hand, asserts that no effect exists or that there is no difference between groups being studied. This allows researchers to perform statistical tests to evaluate whether to reject the null hypothesis in favor of the alternative hypothesis, which proposes that a significant effect or difference does exist.

This framework is essential for conducting experiments and ensuring that conclusions drawn from data are statistically valid and not merely the result of random variation. The null hypothesis thus plays a crucial role in scientific research, providing a clear criterion against which experimental results can be measured.