Final answer:
The p-value represents the probability that the observed test statistic is equal to or more extreme than the one observed, assuming that the null hypothesis is true.
Step-by-step explanation:
The p-value represents the probability that the observed test statistic is equal to or more extreme than the one observed, assuming that the null hypothesis is true. If the p-value is small, it suggests that the observed data is unlikely to occur if the null hypothesis is true, leading to the rejection of the null hypothesis. In this case, a p-value of 0.15 means that there is a 15% chance of obtaining a test statistic as extreme or more extreme than the one observed, assuming the null hypothesis is true.