In the approach of Ronald Fisher, the null hypothesis H0 will be rejected when the "p"-value of the test statistic is sufficiently extreme (vis-a-vis the test statistic's sampling distribution) and thus judged unlikely to be the result of chance. This is usually done by comparing the resulting p-value with the specified significance level, denoted by formula_1, when computing the statistical significance of a parameter"." In a one-tailed test, "extreme" is decided beforehand as either meaning "sufficiently small" "or" meaning "sufficiently large" – values in the other direction are considered not significant. One may report that the left or right tail probability as the one-tailed p-value, which ultimately corresponds to the direction in which the test statistic deviates from H0. In a two-tailed test, "extreme" means "either sufficiently small or sufficiently large", and values in either direction are considered significant. For a given test statistic, there is a single two-tailed test, and two one-tailed tests, one each for either direction. When provided a significance level formula_1, the critical regions would exist on the two tail ends of the distribution with an area of formula_3 each for a two-tailed test. Alternatively, the critical region would solely exist on the single tail end with an area of formula_1 for a one-tailed test. For a given significance level in a two-tailed test for a test statistic, the corresponding one-tailed tests for the same test statistic will be considered either twice as significant (half the "p"-value) if the data is in the direction specified by the test, or not significant at all ("p"-value above formula_1) if the data is in the direction opposite of the critical region specified by the test.