A p-value represents the probability of obtaining results as extreme as the observed data, assuming the null hypothesis is true. A smaller p-value indicates stronger evidence against the null hypothesis. Typically, if the p-value is less than the chosen significance level (such as 0.05), the null hypothesis is rejected. It does not measure the size or importance of an effect, only the strength of the evidence. Many learners seek extra clarity on this topic through academic support options like Pay someone to take my statistics class when concepts feel challenging.