In statistics, a two-tailed test is a method in which the critical region of a distribution is two-tailed and tests whether the sample is larger or smaller than a range of values.
It is used in null hypothesis testing and statistical significance testing.
If the sample being tested falls within one of the critical regions, the alternative hypothesis is accepted instead of the null hypothesis.
By convention, two-tailed tests are used to determine significance at the 5% level, which means that each side of the distribution is reduced by 2.5%.