By the end of the semester you should be able to
1) recognize different types of experiments
2) estimate and test linear combinations of parameters, treatment means, and variance components
3) understand and incorporate fixed and random effects, factorial and nested treatment structures, and polynomial regression terms.

Content

This course covers some basic principles for designing experiments, topics related to linear models for an analysis of variance and analysis of covariance, and conducting an appropriate analysis of data from several types of experiments: completely randomized, randomized complete block, split plot and cross-over.

Modes of study

Participation in classroom work, exam.

Recommended preceding studies

MTTTP1 Introduction to Statistics or other basic course in Statistics.

Fundamental Concepts in the Design of Experiments, Charles R. Hicks, Kenneth V. Turner Jr.