What does the Null Hypothesis represent in hypothesis testing?

The Null Hypothesis represents a baseline or default position in hypothesis testing, asserting that there is no significant effect or difference between groups or conditions being examined. By stating that the status quo is maintained, the Null Hypothesis serves as the foundation for statistical testing. It is a way to quantify and assess the evidence against it in favor of the alternative hypothesis, which posits that there is a difference or effect present.

In practice, researchers aim to either reject or fail to reject the Null Hypothesis based on the sample data collected and the predetermined significance level. If the evidence gathered suggests a statistically significant effect, the null may be rejected, indicating that there is sufficient reason to accept the alternative hypothesis instead. Thus, the primary role of the Null Hypothesis is to provide a clear benchmark against which the effectiveness or impact of new variables can be tested.