Students are introduced to a hands-on approach to analyzing data using R. Topics will include: fundamental statistical concepts such as visualizing data, parameter estimation, p-value interpretation, effect size, model assumptions and model selection, as well as specific tests including t-test, general linear models (including ANOVA and linear regression), generalized linear models, and multivariate techniques.