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Chapter 25: Paired Samples and Blocks. AP Statistics. Paired/Matched Samples. This situation arises when your groups are NOT independent. What are common situations where this occurs Compare subjects with themselves before and after treatment
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Chapter 25: Paired Samples and Blocks AP Statistics
Paired/Matched Samples • This situation arises when your groups are NOT independent. • What are common situations where this occurs • Compare subjects with themselves before and after treatment • Compare subjects with themselves on different variables • NEED TO THINK!!!!!!!!!!
Logic • If the groups are not Independent, you CANNOT use a 2-Sample Test for Means (2-Sample t-Test) • If the groups are Paired/Matched, you are looking at the differences in the variables and that mean difference • Since you are now only looking at one variable (difference in variables), you will perform a one-sample t-test.
Intervals and Tests • When you groups are paired/matched, the intervals you create and the tests you perform are IDENTICAL (mostly) to the intervals you create and the tests you perform for ONE-SAMPLE T-INTERVAL and ONE-SAMPLE T-TEST
Assumptions/Conditions Independence Assumption: • Randomization Condition • 10% Condition Normal Population Assumption: Need to check each group for normality. SHOW GRAPH. Nearly Normal Condition Paired Data Assumption Check reasonableness of this claim. BE CAREFUL
Things to remember • It is about the differences in the variables • The null hypothesis is typically written as: • Once you start the “mechanics” of the problem, you will be looking at things like • You are still dealing with a t-model • Don’t use a two-sample t-test for paired data. • Don’t use a paired –t method when the data are not paired
Calculator Help For a pairedt test, use the same application as for a one-sample t-test or one-sample t-interval.