When a researcher posits no relationship exists between variables, it refers to:

When a researcher posits that no relationship exists between variables, they are formulating a null hypothesis. The null hypothesis serves as a foundational concept in statistical testing, suggesting that any observed effect or relationship in the sample data is due to random variation rather than a true effect in the population.

In research, establishing a null hypothesis is crucial because it provides a benchmark against which other hypotheses can be tested. If researchers find sufficient evidence to reject the null hypothesis through statistical analysis, they can conclude that there is a statistically significant effect or relationship present.

The null hypothesis is distinct from other types of hypotheses. A directional hypothesis would predict a specific direction of the relationship between variables (e.g., one variable increases as another increases), while a non-directional hypothesis indicates that a relationship exists but does not specify its direction. A qualitative hypothesis pertains to data that is descriptive rather than numerical. These distinctions clarify why the correct answer focuses on the null hypothesis as representing the assertion that no relationship exists between the variables of interest.