What is typically indicated by a low p-value in hypothesis testing?

A low p-value in hypothesis testing indicates strong evidence against the null hypothesis. The p-value measures the probability of observing the test results, or something more extreme, given that the null hypothesis is true. When this probability is low, it suggests that the observed data is unlikely under the assumption of the null hypothesis. As a result, researchers may reject the null hypothesis in favor of the alternative hypothesis, which is consistent with the evidence presented by the data.

In statistical practice, a commonly used threshold for a low p-value is 0.05. If the p-value falls below this threshold, it typically leads to the conclusion that there is significant evidence against the null hypothesis. This process is crucial for drawing meaningful inferences from experimental data and supporting or rejecting specific hypotheses based on empirical findings.