The **d****e****p****e****n****d****e****n****t****-****s****am****p****l****e****s ****t ****t****e****s****t **(sometimes called the paired-samples
*t *test) is used to compare two means for the same sample tested at two different times or under two different conditions. This makes it appropriate for pretest-posttest designs or
within-subjects experiments. The null hypothesis is that the means at the two times or under the two conditions are the same in the population. The alternative hypothesis is that they are not
the same. This test can also be one-tailed if the researcher has good reason to expect the difference goes in a particular direction.

It helps to think of the dependent-samples *t *test as a special case of the one-sample *t*test. However, the first step in the dependent-samples *t*test is to reduce
the two scores for each participant to a single **d****i****ffe****r****e****n****c****e ****s****c****o****r****e **by taking the difference between them. At this point, the dependent- samples *t*test becomes a
one-sample *t *test on the difference scores. The hypothetical population mean () of
interest is 0 because this is what the mean difference score would be if there were no difference on average between the two times or two conditions. We can now think of the null hypothesis as
being that the mean difference score in the population is 0 ( = 0) and the alternative hypothesis as being that the mean difference score
in the population is not 0 ( ≠ 0).

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