What does it mean if the null hypothesis is rejected?

Rejecting the null hypothesis indicates that the statistical analysis has provided enough evidence to conclude that there is a significant effect or relationship present in the data, beyond what might be expected by chance alone. This is a foundational concept in hypothesis testing, where the null hypothesis typically posits that there is no effect or no difference. When the null hypothesis is rejected, it suggests that the results observed in the data are unlikely to have occurred under the assumption that the null was true, typically assessed through a predetermined significance level.

This process allows researchers to infer that there is significant evidence supporting an alternative hypothesis, which may propose that a certain treatment, condition, or variable does indeed have an impact. The rejection of the null hypothesis does not confirm the alternative hypothesis as true but rather indicates statistical significance, warranting further investigation or consideration of the effects involved.