In statistical hypothesis testing, the p-value's the probability of obtaining a result at least as extreme as the one that was actually observed, assuming that the null hypothesis's true. The fact that p-values are based on this assumption's crucial to their correct interpretation. The lower the p-value, the less likely the result, assuming the null hypothesis, so the more "significant" the result, in the sense of statistical significance – one often uses p-values of 0.05 or 0.01, corresp… (More on P-value)