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I'm clear on the following:

If there are two different samples, and you wish to test whether they come from the same population we go with an unpaired t-test.

If it is a single sample and we are measuring a scenario of before/after and wish to compare the significance of the results we go with a paired t-test.

However, I'm faced with a situation where I have TWO different samples of equal size, but they are paired based on a common quality. One undergoes treatment and the other sample doesn't. My intuition says I should go for a paired t-test, since there is a 1-1 pairing within the samples.

In most examples I've looked up, the paired t-test is generally used when the sample is the same.

EDIT: By pairing by a common quality I mean the candidates in the two groups are paired by a common attribute, like say equal height, or weight etc.

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It's completely reasonable to use a paired t-test when the two samples are not the same individuals, as long as they are meaningfully paired in some way. Conducting an independent samples t-test and a paired t-test asks very different questions, though.

An example, to illustrate

Let's say you want to test whether teenagers differ from their parents in political orientation, assuming a simplified left-right continuous political scale where 0 means far right and 10 means far left. In general, parents and their children will probably be relatively close to each other on the scale (i.e. conservative parents will be more likely to have conservative kids, and liberal parents will be more likely to have liberal kids). But perhaps teens tend to be more left-leaning than their parents, so the child of a conservative parent may be a little less conservative, and the child of a liberal parent may be even a little more liberal.

If you conduct an independent samples t-test, it will answer the question "Do parents, overall, differ in political orientation from teens, overall?" It will test whether the mean political orientation in parents is different from the mean political orientation in teens. A paired t-test will answer the question "Do teens differ in political orientation from their parents?" It will test whether the mean difference in political orientation for all of the parent-teen pairs is different from zero.

Your data

It's not clear from your description whether you want to look for overall differences between the means of the two samples, or whether you want to know about the difference scores for each matched pair. It is completely reasonable to conduct either the independent or paired analysis --- you should select whichever one will best answer your research question.

Another option which might feel more intuitive for you, depending on how this "matching" process worked, is an ANCOVA. You can control for the matching variable (height, weight, whatever), and look for differences between the groups after partialing out that variable.

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  • $\begingroup$ Thanks for the explanation!! It clears up the confusion! I need to go with the paired test as I'm more concerned about the difference between each matched pair! $\endgroup$ – Joshua1729 Jul 16 '17 at 17:48

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