Description

Experimental designs is one of the most
fundamental tools in the statistical analysis toolbox that allow
practitioners to obtain the best combination of factor levels used to
compare and analyse the treatment responses while optimising the
resources. This course is concern with the designs and statistical
techniques necessary to make valid inferences in the context of
experimental studies.

Prerequirements

Undergraduate course in regression and/or experimental designs.

Tentative course outline

1. Basic principles of experimental designs
2. Review of one factor experiments
3. Full factorial experiments at two levels
4. Fractional factorial experiments at two levels
5. Split-plot designs
6. Factorial experiments with more than two levels
7. Response surface methodology
8. Optimal designs
9. Robust parametric designs
10. Robust parameter designs for signal--response systems
11. Experiments with non-normal data.

References

• DC Montgomery, Design and analysis of experiments, 8th ed., Wiley, 2012.
• CFJ Wu, and MS Hamada, Experiments – planning, analysis, and parameter design optimization, 2nd ed., Wiley, 2009.
• MS Phadke, Quality engineering using robust design. Prentice-Hall, 1989.
• GEP Box, JS Hunter, and WG Hunter, Statistics for experimenters – design, innovation and discovery, 2nd ed.,Wiley, 2005.