ENVS278 Chapter Notes - Chapter 22: Confidence Interval

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An example of paired data would be having the times for each of the skaters in a race in each lake for each race. The races are run in pairs so they can be independent and since they are not independent we cant use the two-sample t methods instead we can focus on differences in times for each race pairing. It is the differences that we care about, this way we are able to have one column to worry about, then you can use a simple one sample t-test. Mechanically a paired t-test is just a one-sample t-test for the means of these pair wise differences. Paired data condition: the data must be qualitative and paired. Independence assumption: if the data are paired, the groups are not independent. For these methods it"s the differences that must be independent from eachother: simple randomization can prevent both bias and produce independence where needed in a design.

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