What does a high p-value indicate about the null hypothesis?

A high p-value indicates that the evidence against the null hypothesis is weak. In statistical hypothesis testing, the null hypothesis represents a default position that there is no effect or no difference in the context of the study. When the p-value is high, it suggests that the data observed is consistent with what we would expect to see if the null hypothesis were true.

In practical terms, a high p-value (typically greater than a significance level, such as 0.05) implies that there is not enough statistical evidence to reject the null hypothesis. This does not mean that the null hypothesis is definitively true, but rather that the data does not provide strong enough evidence to support its rejection. In essence, it suggests that the outcomes of the study could reasonably be attributed to random chance, and thus the null hypothesis remains a plausible explanation.

This understanding is crucial for interpreting statistical results in research and helps inform whether further analysis or data collection is needed in light of the findings.