In statistics, a two-tailed test is a method in which the critical area of a distribution is two-sided and tests whether a sample is greater or less than a range of values. ... If the sample being tested falls into either of the critical areas, the alternative hypothesis is accepted instead of the null hypothesis.

What is an example of a two tailed test?

For example, let's say you were running a z test with an alpha level of 5% (0.05). In a one tailed test, the entire 5% would be in a single tail. But with a two tailed test, that 5% is split between the two tails, giving you 2.5% (0.025) in each tail.

How do you know if a test is one sided or two-sided?

A one-tailed test has the entire 5% of the alpha level in one tail (in either the left, or the right tail). A two-tailed test splits your alpha level in half (as in the image to the left). Let's say you're working with the standard alpha level of 0.5 (5%). A two tailed test will have half of this (2.5%) in each tail.