A shoe company is studying how many shoes Italian men and women own. In one research study they take a random sample of Italian adults and ask each individual if they identify as a man or women and how many pairs of shoes they own. The men and women in this study are in two independent groups. In a second study the researchers use a different design.
This time they take a random sample of heterosexual married couples in Italy i. They record the number of shoes owned by each husband and each wife. This is an example of a matched pairs design. They could collect data in two ways: Sample the blood pressures of the same people before and after they receive a dose.
The two samples are dependent because they are taken from the same people. The people with the highest blood pressure in the first sample will likely have the highest blood pressure in the second sample.
Give one group of people an active drug and give a different group of people an inactive placebo, then compare the blood pressures between the groups. These two samples would likely be independent because the measurements are from different people. What are the hypotheses of an unpaired t-test? What are the assumptions of an unpaired t-test? When to use an unpaired t-test? Paired vs unpaired t-test The key differences between a paired and unpaired t-test are summarized below. A paired t-test is designed to compare the means of the same group or item under two separate scenarios.
An unpaired t-test compares the means of two independent or unrelated groups. In an unpaired t-test, the variance between groups is assumed to be equal. In a paired t-test, the variance is not assumed to be equal. Paired vs unpaired t-test table.
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