In an ANOVA design, the total sum of squares refers to: a. The overall amount of
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In an ANOVA design, the total sum of squares refers to: a. The overall amount of variability in the data set that’s due to our experimental manipulations. b. The overall amount of variability in the data set that is not due to our experimental manipulations( that is error variance) c. The overall amount of variability in the data set d. The overall amount of variability due to the effect of factor A and factor B, but not their interaction In an ANOVA design, the total sum of squares refers to: a. The overall amount of variability in the data set that’s due to our experimental manipulations. b. The overall amount of variability in the data set that is not due to our experimental manipulations( that is error variance) c. The overall amount of variability in the data set d. The overall amount of variability due to the effect of factor A and factor B, but not their interaction a. The overall amount of variability in the data set that’s due to our experimental manipulations. b. The overall amount of variability in the data set that is not due to our experimental manipulations( that is error variance) c. The overall amount of variability in the data set d. The overall amount of variability due to the effect of factor A and factor B, but not their interactionExplanation / Answer
In an ANOVA design, the total sum of squares refers to:
The overall amount of variability in the data set.
Note: Total sum of squares is denoted by SSTotal
SSTotal = SSBetween + SSWithin
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