We discovered the interaction model today. When there are three or more variables present, interaction occurs when at least two of them combine in a way that affects the third variable in a way that is not just additive. In other words, the interaction between the two variables causes their combined effect to be greater than the total of their individual effects. When the impact of one variable depends on the value of another variable, this is known as an interaction effect.
Understanding and accounting for complex relationships in data requires the use of interaction models. They aid in identifying trends and improving the interpretation of the connections between the variables in their data.