In hypothesis testing, the p-Value is the probability that an observed difference between two or more samples *could have occurred by random chance*. Before a hypothesis test is conducted, the experimenter decides on an acceptable level of α risk, and the p-Value must be lower than the α risk in order to conclude that a true change has taken place.

Generally a p-Value of less than 0.05 is considered acceptable for concluding that a statistically significant change has taken place.