PSYC 3430 Lecture Notes - Lecture 4: Null Hypothesis, Explained Variation, Repeated Measures Design
3 Oct 2017
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13. 3 hypothesis testing and effect size with the repeated-measures anova. Calculation of the variances (ms values) and the f-ratio. In the literature - reporting the results of a repeated-measures anova. Individual differences and the consistency of the treatment effects. Learning objectives and chapter summary: students should understand the logic underlying the analysis of variance for a repeated- measures study. The denominator of the f-ratio is intended to measure differences (or variance) that occur simply by chance. These chance differences are the unsystematic, unpredictable differences that are not caused by a treatment effect or some other systematic and predictable source. In an independent-measures study where every score comes from a different person, the naturally occurring differences from one person to another (individual differences) are unpredictable and are included in the category of chance or error variance. In a repeated-measures study, however, the differences from one person to another are often systematic and predictable.
