A p-value is a statistical measure that helps researchers determine whether their results are statistically significant. It is commonly used in hypothesis testing to determine the likelihood of obtaining a result that is at least as extreme as the one that was observed, given that the null hypothesis is true. A small p-value (usually less than 0.05) indicates that the observed result is unlikely to have occurred by chance, and therefore provides evidence against the null hypothesis. In other words, a small p-value suggests that the observed result is statistically significant and supports the alternative hypothesis. In contrast, a large p-value (greater than 0.05) indicates that the observed result is not statistically significant and does not support the alternative hypothesis.