A two-tailed test is an approach to hypothesis testing where researchers reject the null hypothesis if their calculated test statistic falls into the extreme regions of either the positive or negative tail of the distribution. This method utilizes two distinct critical values—an upper bound and a lower bound—and is appropriately chosen when researchers expect the sample mean to differ from the hypothetical population mean, but lack strong theoretical justification to predict whether it will be higher or lower.