In most of the XLSTAT statistical test dialog boxes, the user is able to choose between two-tailed or one-tailed tests (Options tab, usually). In the example described above, the alternative hypothesis related to a one-tailed test could be written as follows: average(A) average(B), depending on the expected direction of the difference. One-tailed testsĪ One-tailed test is associated to an alternative hypothesis for which the sign of the potential difference is known before running the experiment and the test. Two-tailed tests are by far the **most commonly used tests. ![]() This drives us to choose a two-tailed test, associated to the following alternative hypothesis: Ha: average(A) ≠ average(B). Before setting up the experiment and running the test, we expect that if a difference between the two averages is highlighted, we do not really know whether A would be higher than B or the opposite. For example, suppose we wish to compare the averages of two samples A and B. Two-tailed testsĪ Two-tailed test is associated to an alternative hypotheses for which the sign of the potential difference is unknown. ![]() ![]() The type of alternative hypothesis Ha defines if a test is one-tailed or two-tailed. ![]() A statistical test is based on two competing hypotheses: the null hypothesis H0 and the alternative hypothesis Ha.
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