What does a low p-value indicate in hypothesis testing?

A low p-value indicates strong evidence against the null hypothesis. In the context of hypothesis testing, the p-value represents the probability of observing the data, or something more extreme, assuming the null hypothesis is true. When the p-value is low (typically below a significance level such as 0.05), it suggests that the observed results would be highly unlikely under the null hypothesis. This leads researchers to reject the null hypothesis in favor of the alternative hypothesis, which posits a significant effect or difference. Essentially, a low p-value means that the evidence collected points toward the existence of an effect, warranting further consideration against the null hypothesis.