In this talk, I will present an approach for developing students' intuition about the impact of correlated outcomes that can be used during a course on statistical methods for correlated data. This approach is centered around an in-class activity that students complete during the first week using results from Monte Carlo simulations to illustrate what goes wrong when correlated outcomes are analyzed using standard statistical methods that assume independent outcomes. Once students develop intuition around why non-standard regression techniques (e.g., linear mixed effect models) are needed to provide proper inference, they are more invested in learning about these methods in the remainder of the course. Additionally, I will discuss how this intuition gained from the activity can be integrated throughout the course. This activity has been implemented with success twice at the beginning of a graduate course on statistical methods for analyzing correlated data taken by students with limited mathematical backgrounds.