In statistics, Interaction describes the situation in which two Predictor Variables combine to have a more than independent or additive effect on a Dependent Variable. See example given in Dependent Variable:
Where you have more than one predictor variable you have the possibility of an “interaction”: for example both being male and being unemployed might be associated with early opting out, say each doubles the likelihood of early opt out. However, the relationship might be more than additive and being both male and unemployed might raise the likelihood of early termination eight times.

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Dependent variable
Predictor variable
Independent variable

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Chapter 5.

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