This course develops fundamental concepts and methodology in the design and analysis of experiments. Topics include analysis of variance, multiple comparison tests, completely randomized designs, the general linear model approach to ANOVA, randomized block designs, Latin square and related designs, completely randomized factorial designs with two or more treatments, hierarchical designs, split-plot and confounded factorial designs, and analysis of covariance. Conceptual discussion in lectures is supplemented with hands-on practice in applied data-analysis tasks using SAS or R statistical software.