Which research hypothesis denotes no expected effect or relationship between variables?

The null hypothesis serves as a foundational concept in statistical testing and research design. It represents a statement of no effect or no relationship between variables, suggesting that any observed differences are due to random chance rather than a true effect. In hypothesis testing, the null hypothesis is typically denoted by H0, and researchers seek to either reject or fail to reject this hypothesis based on empirical data.

Understanding the null hypothesis is critical in evidence-based practice because it establishes a baseline against which other hypotheses can be tested. When researchers formulate their questions or design experiments, they often propose an alternative hypothesis, which posits that there is a significant effect or relationship. The null hypothesis provides a clear framework for testing these claims, using statistical methods to determine whether there's sufficient evidence to reject H0 in favor of the alternative hypothesis.

In contrast, a directional hypothesis proposes a specific direction of the expected relationship or effect, while a simple hypothesis states the relationship between two variables without indicating whether it's positive or negative. Both differ fundamentally from the null hypothesis in that they indicate an expected relationship or effect rather than denying its existence.