Design of Experiments

Module overview

When planning experiments, it is essential that the data collected are as relevant and informative as possible. The statistical principles for the design of experiments include the choice of optimal or good treatments sets and appropriate replication of them, randomization to ensure unbiasedness and the use of blocking and other methods for reduction of variance

Linked modules

Pre-requisites: MATH6174 or STAT6123 or (MATH2011 and MATH2010)

Learning and Teaching

Teaching and learning methods

Lectures, problem classes and self-directed computer work

Study time
Type	Hours
Problem Classes	12
Lecture	36
Independent Study	102
Total study time	150

Resources & Reading list

General Resources

Website on Blackboard.

Textbooks

Max D. Morris (2011). Design of Experiments: An Introduction Based on Linear Models. CRC Press.

John, J.A. and Williams, E.R. (1995). Cyclic and computer generated designs. London: Chapman and Hall.

Box, G.E.P., Hunter, J.S. and Hunter, W.G. (2005). Statistics for Experimenters. New York: Wiley.

Mead, R, Gilmour, SG, and Mead, A (2012). Statistical Principles for the Design of Experiments. Cambridge.

Atkinson, A.C., Donev, A.N. and Tobias, R.D. (2007). Optimum Experimental Designs, with SAS. Oxford: Oxford Science Publication.

Montgomery, D.C. (2009). Design and Analysis of Experiments. New York: Wiley.

Wu, C.F.J. and Hamada, M. (2009). Experiments - Planning, Analysis and Parameter. New York: Wiley.

Dean, A.M. and Voss, D.T. (1999). Design and Analysis of Experiments. New York: Springer-Verlag.

Assessment

Formative

This is how we’ll give you feedback as you are learning. It is not a formal test or exam.

Exercises and Quizzes

Assessment Type: Formative
Feedback:
Final Assessment: No
Group Work: No

Summative

This is how we’ll formally assess what you have learned in this module.

Breakdown
Method	Percentage contribution
Coursework	50%
Written assessment	50%

Referral

This is how we’ll assess you if you don’t meet the criteria to pass this module.

Breakdown
Method	Percentage contribution
Written assessment	100%

Repeat

An internal repeat is where you take all of your modules again, including any you passed. An external repeat is where you only re-take the modules you failed.

Breakdown
Method	Percentage contribution
Written assessment	50%
Coursework	50%

Repeat Information

Repeat type: Internal & External