Null hypotheses, also known as H0, are statements or assumptions used in statistical hypothesis testing that assert that there is no significant difference, effect, or relationship between variables. It implies, therefore, that any observed differences or associations in the data are due to chance, not systematic or meaningful patterns.
Researchers formulate a null hypothesis based on the research question or problem they intend to investigate. It represents a default position that they hope to challenge or reject through statistical analysis. Alternative hypotheses (denoted as H1 or Ha) suggest a significant difference, effect, or relationship between the two variables.
As a matter of fact, failing to reject the null hypothesis does not mean the null hypothesis is true; rather, it means there isn’t enough evidence to support the alternative hypothesis.
In order to interpret the results, the research question and context must be considered. In order to gain a deeper understanding of the phenomenon being studied, researchers may choose to continue investigating, refine the design, or collect more data.