Designed for a two-semester, introductory course for graduate students in the social sciences, this text introduces three major advances in the field: 1) sample size estimation needed to justify normality via the central limit theorem, 2) the impact of outliers and heavy-tailed distributions on power and our ability to obtain an accurate assessment of how groups differ and variables are related, and 3) the deleterious effects of heteroscedasticity on conventional ANOV A and regression methods. Focusing on conceptual issues rather than complex computational details, it also provides a library of R functions.