AMS 582: Design of Experiments
Discussion of the accuracy of experiments, partitioning sums of squares, randomized designs, factorial experiments, Latin squares, confounding and fractional replication, response surface experiments, and incomplete block designs.
Required Textbook: Design and Analysis of Experiments by Douglas C. Montgomery, 10th edition, 2020, Wiley
Supplementary Textbooks:
- Applied Linear Statistical Models by Michael H. Kutner, Christopher J. Nachtsheim, John Neter and William Li, 5th edition, 2013, McGraw Hill
- Statistics for Experimenters: Design, Innovation, and Discovery by George E. P. Box, J. Stuart Hunter and William G. Hunter, 2nd edition, 2005, Wiley
- The Design of Experiments by Ronald A. Fisher, 9th edition, 1971, Hafner Press
- Experiments: Planning, Analysis, and Parameter Design Optimization by C. F. Jeff Wu and Michael Hamada, 2000, Wiley
- The Analysis of Variance by Henry Scheffé, 1999, Wiley
Learning Outcomes
- Extend knowledge of probability theory.
- Central chi-square and central F-distributions;
- Non-central chi-square and non-central F-distributions;
- Multiple comparisons procedures including Bonferroni’s inequality, Scheffe’s multiple comparison procedures, and Tukey’s multiple comparison procedures;
- Decomposing chi-square sums of squares;
- Expected value and variance of sums of squares.
- Learn classical statistical designs:
- One-way layout;
- Randomized block designs;
- Latin squares, Graeco-Latin squares, hyper Graeco-Latin squares including designs with replications;
- Two and three way layouts;
- $2^k$ designs;
- Random effect models;
- Mixed models.
- Power and sample size computations.
- Learn the statistical computing package of the student’s choice and apply it to obtain the statistical model that generated a set of synthetic data.