What is the difference between a paired and unpaired hypothesis test? Why is a T
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What is the difference between a paired and unpaired hypothesis test? Why is a T-test NOT used to test multiple means (more than 2)? A random iPhone assembly plant has been selected for quality assessment. It will be testing its 4 assembly lines to see if they differ with respect to the amount of defective phones produced. Independent samples of 30 phones are collected from each line. The collected data is represented in Table 4. Test the quality assessment at 5% significance. Below are the partial results of an ANOVA table. An automotive parts manufacturer is testing the difference between the average life expectancy for the different brands of fan belts that they sell.Explanation / Answer
9)
Paired t-test compares study subjects at 2 different times (paired observations of the same subject).
Unpaired t-test (aka Student’s test) compares two different subjects.
The paired t-test reduces intersubject variability (because it makes comparisons between the same subject), and thus is theoretically more powerful than the unpaired t-test.
Paired means that you will look at the differences between the two groups. A paired test first calculates the difference from one group to the other, and runs a one-sample t test
If you use a within-subject design, you should use a paired t test. Because each participant contributed to a data point for each of the two groups (e.g., two interaction techniques), your data have an implicit relationship based on your participants. For example, some participants were slower than other participants in both techniques, but all of the participants were faster with one technique than with the other. paired t test considers such individual differences by taking the differences between the two groups. Otherwise, you can't really have a legitimate way to take the differences, so you need to use an unpaired t test.
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