Answers_to_dependent_samples_t-test

Answers_to_dependent_samples_t-test - Difference scores =...

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Answers #1. there is actually just one sample (group) each case is tested twice the same outcome variable is measured each time it analyzes difference (change) scores its numerator is the average change across measurement occasions its degrees of freedom are N-1 It is for a within-subjects (repeated measures) design #2. It is used when you are doing hypothesis testing and you have two scores for each participant (such as before-score and an after-score) and the population variance is unknown. #3. Subtract one from the other to create a difference or change score for each person. The t test is then done with these difference of change scores. #4. (a) 0 (b) Because you are comparing your ample to a situation in which there is no difference- a population of difference scores in which the average difference is 0. #5. t test for dependent means (Matched t test) t needed (df = 4), alpha = .05, 1-tailed = -2.132
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Unformatted text preview: Difference scores = -3, 3, 2, -7, -8 Mean of D = -2.6; Estimated population variance = SS / df = 25.3 Variance of the distribution of means = 25.3 / 5 = 5.06 Standard deviation of the distribution of means = 5.06 = 2.25 Standard error = 2.25 / 5 = 1.00 t = (M - ) / Standard error t = -2.6 0) / 1.00 = - 2.6 Decision: Reject the null hypothesis. The psychologists program does significantly reduce test anxiety. #6. t test for dependent means (Matched t test) t needed (df = 4), alpha = .05, 1-tailed = 2.132 Difference scores = .07, .18, .14, .18, -.13 M = .088; Estimated population variance = SS / df = .017 Variance of the distribution of means = .017 / 5 = .003 Standard deviation of the distribution of means = .003 = .055 Standard error = .025 t = (M - ) / Standard error t = (.088 0) / .025 = 3.52 Decision: Reject the null hypothesis. There is a difference in time for the kinds of words....
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Answers_to_dependent_samples_t-test - Difference scores =...

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