In statistical hypothesis testing, statistical significance (or a statistically significant result) is attained when a p-value is less than the significance level (denoted α, alpha). The p-value is the probability of obtaining at least as extreme results given that the null hypothesis is true whereas the significance level α is the probability of rejecting the null hypothesis given that it is true. Equivalently, when the null hypothesis specifies the value of a parameter, the data are said to be statistically significant at given confidence level γ = 1 − α when the computed confidence interval for that parameter fails to contain the value specified by the null hypothesis.