Final Answer:
Interaction terms refer to the inclusion of variables in a statistical model to account for their combined effect on the dependent variable. They capture the joint influence and potential synergy between two or more variables. In statistical modeling, interaction terms are crucial for understanding how the relationship between the independent variables and the dependent variable may change based on the presence or absence of other variables.
Step-by-step explanation:
Interaction Terms Definition:
Interaction terms involve incorporating variables into a model to assess their collective impact on the dependent variable. This encapsulates the idea that the effect of one variable can be modified by the presence of another.
Capturing Joint Influence:
Interaction terms allow us to capture and analyze the joint influence of multiple variables. This is particularly relevant when there's a suspicion that the combined effect of variables is not simply additive.
Changing Relationships:
In statistical models, interaction terms help uncover how the relationship between independent and dependent variables changes based on the levels or values of other variables. This is vital for a nuanced understanding of complex relationships.