The p-value is another fundamental concept in hypothesis testing. It represents the probability of obtaining the observed results, or more extreme ones, assuming that the null hypothesis is true. If the p-value is less than or equal to the significance level (α), the null hypothesis is rejected. In other words, a low p-value indicates that the observed data is unlikely under the null hypothesis, leading to its rejection.
