What does the p-value indicate?

The p-value serves as a crucial indicator in hypothesis testing, reflecting the likelihood of obtaining the observed sample results—or something more extreme—if the null hypothesis is true. This probability helps researchers determine whether to reject the null hypothesis. A lower p-value suggests that the observed data are less likely under the null hypothesis, possibly indicating that there is enough evidence to conclude that there is an effect or a relationship present.

In contrast, the other options do not accurately define the p-value. Some options focus on aspects of relationships between variables or the variability in datasets, which relate to different statistical measures such as correlation or standard deviation, rather than the specific probability provided by the p-value. The effect size, meanwhile, pertains to the magnitude of a relationship or treatment effect and is not indicated by the p-value itself.