Final answer:
The combined effect of two or more independent variables on one or more dependent variable is known as the interaction effect. Regression analysis can be used to examine the interaction effect.
Step-by-step explanation:
The combined effect of two or more independent variables on one or more dependent variable is known as the interaction effect. It refers to how the relationship between the independent variables and the dependent variable changes when they are considered together.
For example, let's say we are investigating the effect of both temperature and humidity on plant growth. If the effect of temperature on plant growth is different depending on the level of humidity, we have an interaction effect.
Regression analysis can be used to examine the interaction effect by including interaction terms in the regression model.