What is an interaction?

What is an interaction?

• A. When the effect of one factor depends on the levels of a second factor.
• B. When the effect of two factors adds up independently.
• C. When there is no relationship between the factors.
• D. When a single factor affects the dependent variable equally at all levels.

Answer: (A)

In factorial designs, an interaction means the effect of one factor on the outcome changes depending on the level of another factor. For example, if a study looks at teaching method (interactive vs lecture) and student motivation (high vs low), an interaction occurs when the interactive method boosts scores much more for highly motivated students than for those with low motivation. The method doesn’t have a uniform impact across motivation levels. If the two factors simply add their effects, with the method helping by the same amount at every motivation level, there’s no interaction—the effects are independent and additive. You can often spot an interaction by plotting the results: the lines for one factor across the levels of the other factor are not parallel. In analysis, a significant interaction term in ANOVA signals that you should interpret the simple effects within each level rather than rely on main effects alone.

In factorial designs, an interaction means the effect of one factor on the outcome changes depending on the level of another factor. For example, if a study looks at teaching method (interactive vs lecture) and student motivation (high vs low), an interaction occurs when the interactive method boosts scores much more for highly motivated students than for those with low motivation. The method doesn’t have a uniform impact across motivation levels.

If the two factors simply add their effects, with the method helping by the same amount at every motivation level, there’s no interaction—the effects are independent and additive. You can often spot an interaction by plotting the results: the lines for one factor across the levels of the other factor are not parallel. In analysis, a significant interaction term in ANOVA signals that you should interpret the simple effects within each level rather than rely on main effects alone.