Violations of assumptions, inflated Type I error rates, and robustness are important concepts for students to learn in an introductory statistics course. However, these abstract ideas can be difficult for students to understand. Monte Carlo simulation methods can provide a concrete way for students to learn abstract statistical concepts. This article describes the MC4G computer software (Brooks, 2004) and the accompanying instructor's manual (Raffle, 2004). It also provides a case study that includes both assessment and course evaluation data supporting the effectiveness of Monte Carlo simulation exercises in a graduate-level statistics course.