Abstract
In aspiring to be discerning epidemiologists, we must learn to think critically about the fundamental concepts in our field and be able to understand and apply many of the novel methods being developed today. We must also find effective ways to teach both basic and advanced topics in epidemiology to graduate students, in a manner that goes beyond simple provision of knowledge. Here, we argue that simulation is one critical tool that can be used to help meet these goals, by providing examples of how simulation can be used to address 2 common misconceptions in epidemiology. First, we show how simulation can be used to explore nondifferential exposure misclassification. Second, we show how an instructor could use simulation to provide greater clarity on the correct definition of the P value. Through these 2 examples, we highlight how simulation can be used to both clearly and concretely demonstrate theoretical concepts, as well as to test and experiment with ideas, theories, and methods in a controlled environment. Simulation is therefore useful not only in the classroom but also as a skill for independent self-learning.