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T-Test (Dependent Measures)

T-Test (Dependent Measures). Hypothesis Testing. If the null hypothesis is true, this is the expected distribution of means: Does my actual sample fall in the “more likely” area?. More Likely Outcomes. Less Likely Outcomes. When Do We Use. A t-test for independent samples?

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T-Test (Dependent Measures)

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  1. T-Test (Dependent Measures)

  2. Hypothesis Testing • If the null hypothesis is true, this is the expected distribution of means: • Does my actual sample fall in the “more likely” area? More Likely Outcomes Less Likely Outcomes

  3. When Do We Use • A t-test for independent samples? • Two samples (maybe males and females) • Continuous Dependent Variable (maybe height) • We ask “Are the sample means (basically) the same or different?”

  4. What about T test for Dependent Measures • Classic example: • Give a scale before a treatment and then again after. • (Pre test- post test design) • Ask “Did this one group change from the pre-test to the post test?”

  5. Its all about those difference scores • The null hypothesis is the mean of the difference scores is zero

  6. Effect Size • What does the p-test tell us about our results? • What is it we really want to know about the results?

  7. One measure of Effect Size: Cohen’s d D

  8. Cohen’s d • Very simple way of standardizing the effect size

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