11_t_Test_Dependent_Outline - 1 t Test for Two Dependent...

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1 t Test for Two Dependent Samples • Dependent samples • Difference scores • Null and alternative hypotheses • Mean • Standard Error –Effects of dependent samples on SE t ratio • Repeated measures and counter-balancing • Assumptions So far, we’ve discussed . . . t test for one sample t test for two independent samples • Now we turn to . . . t test for two dependent samples Two Dependent Samples • Each observation in one sample is paired with another single observation in the other sample • Generally known as –Dependent, related, or correlated samples • Special cases –Within subjects •Repeated measures –Matched subjects Example • What are the effects of caffeine on memory? Example Dependent Samples • We want to make certain that groups A and B are matched on cognitive factors, such as memory span –e.g., We want to match on basic memory capacity before administering caffeine and placebo • How could we match the participants in the two groups? Dependent Samples • We might test twins 1 2 3 4 5 6 7 8 9
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2 –Matched subjects design Dependent Samples Dependent Samples • Because we're testing twins, the two groups (A and B) should differ little on cognitive factors • We have controlled for possible cognitive differences between A and B Example: Scores on Memory Test after Caffeine (A) or Placebo (B) Difference Scores D : difference score D = X 1 - X 2 ( X 2 X 1 is preferred in text) • Difference between each pair of scores in the two dependent
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11_t_Test_Dependent_Outline - 1 t Test for Two Dependent...

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