When one variable’s impact on an outcome shifts depending on the level of another variable, that’s an interaction effect. This statistical concept reveals hidden dependencies, moving beyond isolated main effects to show how factors combine. Researchers, data scientists, and marketers use it to refine predictive models, personalize strategies, and uncover nuanced insights. Ultimately, anyone analyzing complex systems benefits from identifying these crucial, non-additive relationships.
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