The course begins with a review of sampling, sampling distributions, and simple comparative experiments. Single factor experiments with both fixed and random effects are considered.
Designs illustrated include randomized blocks, latin squares and factorial experiments.
Mixed models and rules for expected mean square are presented. Model adequacy, sample size considerations, power determinations and restrictions on randomization procedures are discussed. The use of statistical software packages is integrated throughout the course. An introduction to least squares estimation in simple and multiple regression models. The matrix approach is used in the more general multiple regression model.