Question

How are paired samples different than un-paired samples? What is the consequence of using a “paired” model for “unpaired” data – and vice versa. Give examples of each situation.

Answer 1

Explanation:

T-tests are useful for comparing the means of two samples. There are two types: paired and unpaired.

Paired means that both samples consist of the same test subjects. A paired t-test is equivalent to a one-sample t-test.

Unpaired means that both samples consist of distinct test subjects. An unpaired t-test is equivalent to a two-sample t-test.

For example, if you wanted to conduct an experiment to see how drinking an energy drink increases heart rate, you could do it two ways.

The "paired" way would be to measure the heart rate of 10 people before they drink the energy drink and then measure the heart rate of the same 10 people after drinking the energy drink. These two samples consist of the same test subjects, so you would perform a paired t-test on the means of both samples.

The "unpaired" way would be to measure the heart rate of 10 people before drinking an energy drink and then measure the heart rate of some other group of people who have drank energy drinks. These two samples consist of different test subjects, so you would perform an unpaired t-test on the means of both samples.