lecture 16 Dependent t0

lecture 16 Dependent t0 - Repeated Measures A more powerful...

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Repeated Measures A more powerful alternative to between- subjects designs Eliminates the between-group variability that arises from random assignment of subjects to conditions Related Samples t Test - performed on the difference scores, rather than the raw scores, from a sample yielding matched pairs of observations for two conditions 1
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Difference Scores Subject X 1 X 2 D = X 1 - X 2 1 53 55 -2 2 62 60 2 3 41 45 -4 4 35 30 5 2
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Related Samples t Test Conditions and assumptions Unknown true mean difference ( μ D ) between two experimental conditions Unknown variance of the difference scores for the population, σ 2 D Sampling distribution for the mean of the difference scores ( μ D ) approximately normal, owing to either a normal population, or a large enough sample size ( n 10 pairs of observations) 3
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The Test Statistic t = (D - μ D hyp )/s D Where D = D/n , the mean of the difference scores μ D hyp is the mean of the difference scores under H 0 s D is the sample estimate of the standard error of the difference scores 4
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lecture 16 Dependent t0 - Repeated Measures A more powerful...

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