Design and Analysis of Experiments ((4))

Catalog description

Statistical principles and concepts in the design and analysis of experiments. Topics include: fixed and random effects models, expected mean squares, multiple comparisons, nonparametric methods, basic designs including completely randomized design, randomized blocks design, incomplete block designs, Latin squares, factorial designs, and nested designs. Use of R or SAS throughout the course. Prerequisite: C- or better in MATH 2200 or MATH 4200 . Recommended: MATH 3210 .