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Interaction in an experiment refers to the phenomenon where the effect of one independent variable on the dependent variable changes depending on the level of another independent variable. This means that the combined influence of two or more variables is different from their individual effects. Identifying interactions is crucial for understanding complex relationships in data and can reveal insights that might be missed when examining variables in isolation.

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