Final answer:
The true statement about interactions is that they occur when X variables affect each other's influence on Y, which signifies that the relationship between an independent variable and the dependent variable can be modified by another independent variable.
Step-by-step explanation:
The correct statement about interactions is: Interactions exist when X variables affect each other's influence on Y. This means that the effect of one independent variable on the dependent variable may depend on the level of another independent variable. In other words, an interaction is present when the relationship between one predictor (X) and the outcome (Y) changes depending on the value of another predictor.
Interpreting interactions can be complex, and it is not always straightforward as multiple variables can affect the relationships in various ways. Interaction is not the same as multicollinearity, which is a condition where two or more independent variables in a regression model are highly correlated. Interactions are also distinct from mere correlations among X variables; rather, they describe a situation where the combined effect of variables on Y is different from the sum of their separate effects.