At the end of this course, successful students will be able to

1. Design and conduct an experiment that exhibits both a treatment design and randomization design that allow for the testing of differences between the levels of a single or multiple treatments of interest.
2. Given a description of an experiment, correctly identify common design elements, including (a) Crossed factorial designs with interactions, (b) Nested factorial designs, (c) Blocking factors, (d) Nuisance variables, (e) Split-plot designs, (f) Repeated measures, and (g) Random effects.
3. Specify an appropriate statistical model for observations resulting from a designed experiment exhibiting the elements in item 2.
4. Identify estimable terms in a statistical model for an experiment, find the least squares estimator of estimable terms, and specify the statistical distribution of the estimator.
5. Conduct and correctly interpret statistical hypothesis tests for the overall effect of a treatment and for the effects of contrasts.
6. Correctly employ methods for multiple comparisons to control the experimentwise error rate when multiple hypothesis tests are conducted.
7. Examine model assumptions using residual plots and a description of the experiment. Apply remedial measures such as transformations to the response when such transformations improve adherence to modeling assumptions.