What is the purpose of the null hypothesis?

The purpose of the null hypothesis is to establish a baseline or default position in statistical hypothesis testing. This hypothesis typically posits that there is no effect, no difference, or no relationship between the variables being studied. By setting this baseline, researchers can use statistical methods to determine whether the evidence from the data is strong enough to reject the null hypothesis in favor of an alternative hypothesis, which suggests that there is an effect or relationship present.

Establishing a default position helps in quantifying the likelihood of observing the data if the null hypothesis were true. It allows researchers to systematically test their theories, providing a framework for making decisions based on empirical evidence. In practical terms, if the analysis shows significant results that contradict the null hypothesis, researchers can draw conclusions about the presence of an effect or relationship, thereby advancing knowledge in that field of inquiry.

The other options, while related to research, don't accurately capture the fundamental role of the null hypothesis in statistical testing. Proposing a relationship between variables suggests the role of the alternative hypothesis, exploring potential outcomes is more aligned with theoretical frameworks prior to establishing testable hypotheses, and providing an alternative to statistical analysis does not fit with the aim of the null hypothesis, which is specifically to serve as a point of reference