In a statistical hypothesis test, the P value is the probability of observing a test statistic at least as extreme as the value actually observed, assuming that the null hypothesis is true. This probability is then compared to the pre-selected significance level of the test. If the P value is smaller than the significance level, the null hypothesis is rejected, and the test result is termed significant; the significance of a statistical test. P-values of less than 0.05 are generally considered to be an indicator that a statistical model is significant; a quantitative estimate of the probability that the observed difference between two groups could have happened by chance alone.