The term analysis of variance is very descriptive of the process we use in the statistical treatment of the data. In a general sense, to analyze something is to examine the individual elements of a whole. In ANOVA, we start with a totality and break it apart – partition it – into portions that we then examine separately.

The totality that we break apart in ANOVA, as you might suspect from the name of the procedure, is the variance of the scores on the dependent variable. As you recall from Chapter 2, variance is equal to the sum of squares – the sum of the squared deviations from the mean – divided by the degrees of freedom. In an ANOVA design, it is the variance of the total set of ...

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