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An interaction term in statistical modeling is a variable that represents the combined effect of two or more independent variables on a dependent variable. It is used to assess whether the impact of one independent variable on the dependent variable changes depending on the level of another independent variable. Interaction terms are often included in regression models to capture complex relationships between predictors, providing deeper insights into how variables interact with each other. For example, in a study examining the effect of diet and exercise on weight loss, an interaction term could show how the effect of diet on weight loss varies at different levels of exercise.

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