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In an independent-samples $$t$$-test, the null hypothesis assumes that the means of the two distinct populations are perfectly equal ($$\mu_1 = \mu_2$$). Conversely, the alternative hypothesis asserts that these two population means are not the same ($$\mu_1 \neq \mu_2$$). Similar to other hypothesis tests, researchers may utilize a one-tailed test if they have a strong theoretical justification to predict that the difference between the groups will occur in a specific direction.

Null and Alternative Hypotheses for the Independent-Samples t-Test

When conducting an independent-samples t-test, what does the null hypothesis assert regarding the two distinct populations?

If a researcher has a strong theoretical justification to predict that one group will score higher than another in an independent-samples t-test, their null hypothesis will assert that the two population means are not the same.

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