In a two-factor ANOVA,the sum of squares due to both factors,the interaction sum of squares,and the error sum of squares must all add up to the total sum of squares.

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This statement is true. The total sum of squares is the variation in the dependent variable, which is partitioned into the sum of squares due to the two factors, the interaction between the two factors, and the error (unexplained) sum of squares. Therefore, the sum of squares due to both factors, the interaction sum of squares, and the error sum of squares must add up to the total sum of squares.

In a Two-Factor ANOVA,the Sum of Squares Due to Both