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When a researcher has two samples with two means one of the assumptions for two samples is independence of between the two samples What does this mean What happens if the independence assumption is?
Wiki User
∙ 13y ago
Independence of the two samples means that the choosing of the first sample did not influence the choosing of the other sample, and vice versa.
For example, if you were comparing running speed in two different brands of running shoes, you could look at two samples of people running a 100 m dash -- one sample of people running in Brand A and one sample of people running in Brand B. If those two groups were picked independently of one another, these samples would be independent. If, instead, you had the same group of people run the race twice (once in each brand of shoe), these samples would be dependent.
Samples that are not independent are said to be "correlated", "interdependent", or "dependent". Because the two samples are correlated, you might get incorrect findings for your statistical study. For example, say you want to compare the heights of boys and girls. If you chose the samples by choosing a girl for the girl sample, then choosing her brother for the boy sample, your statistical analyses might be misleading if you didn't account for the fact that tall girls are more likely to have tall brothers, and short girls are more likely to have short brothers. By choosing siblings for the two groups, you have made the two samples not independent of one another.
If the independence assumption is violated, you have to do a special type of statistical test. For example, instead of doing a two-sample t-test, you would have to do a paired t-test.
Wiki User
∙ 13y ago
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