2 sssubject k m s m 4 subjects s if you

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Unformatted text preview: age score for each subject (instead of the average for each ! easurement), Ms, and calculate the squared differences from the mean. We multiply m each square by k because it represents k raw scores (all the measurements from a single subject), and then add them up. 2 SSsubject = # k ( M s " M ) (4) subjects s If you think of the whole dataset as a matrix, with rows representing subjects and columns representing measurements, then you can see how the formulas for SStreatment and SSsubject ! work in exactly the same way. The only difference is that SStreatment is based on the columns (treatment levels) and SSsubject is based on the rows (subjects). The residual variability is the variability that’s left over after we remove SStreatment and SSsubject. There are ways to compute SSresidual directly, but the formulas are complicated a...
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This document was uploaded on 02/25/2014 for the course PSYC 3101 at Colorado.

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