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2010/1 Module Catalogue
 Module Code: MAT3021 Module Title: EXPERIMENTAL DESIGN
Module Provider: Mathematics Short Name: MS338
Level: HE3 Module Co-ordinator: GODOLPHIN JD Dr (Maths)
Number of credits: 15 Number of ECTS credits: 7.5
 
Module Availability
Spring
Assessment Pattern
                        Unit(s) of Assessment
                        Weighting Towards Module Mark( %)
2 hour unseen examination
75
Test
10
Coursework
15
Qualifying Condition(s) 
A weighted aggregate mark of 40% is required to pass this module.
 
Module Overview
Fundamental topics in the design and analysis of experiments are introduced. For a variety of statistical models, the structure of the model and applications are covered. Particular attention is given to model adequacy checking. Statistical software is used to ensure that the emphasis is on methodological considerations rather than on calculation.
Prerequisites/Co-requisites
MAT2046 Statistics 2 would be useful but is not a pre-requisite.
Module Aims
The principal aims are to expose students to a wide range of statistical designs and concepts and to provide them with the tools to design and analyse appropriate experiments in a range of situations.
Learning Outcomes

At the end of the module a student should have:

 

(1)an appreciation of design consideration and constraints

 

(2)an ability to design and analyse an experiment in a variety of situations.
Module Content

General Concepts:

 

Principles of design and strategy of experimentation Complete designs: m-way classification

 

 

 

Designs Involving Blocking:

 

Precision improvement by blocking

 

Randomized block designs

 

Incomplete block designs and balance

 

Row column designs

 

Euler's conjecture: Graeco-Latin squares Youden squares

 

 

 

Further Topics Involving Blocking:

 

Efficiency

 

Optimality criteria

 

Connectivity

 

 

 

Factorial Designs:

 

Principles and advantages of factorials

 

Two level factorial systems

 

Fractional factorials

 

Confounding in factorials with n factors each at 2 levels

 

 

 

Topics with Specific Applications:

 

Robust design and Taguchi methods

 

Analysis of covariance

 

Binary response data

 

Crossover designs and carryover effects
Methods of Teaching/Learning

Teaching is by lectures and example classes. Learning takes place through lectures, exercises (example sheets) and background reading. 

Spring semester: 3 contact hours per week for 10 weeks. Mainly lectures but including some supervised computer lab sessions.

 
Selected Texts/Journals

Angela Dean and Daniel Voss, Design and Analysis of Experiments, Springer, 1999

 

J.A. John and E.R. Williams, Cyclic and Computer Generated Designs, Chapman and Hall, 1995 Douglas C. Montgomery , Design and Analysis of Experiments, 6th edition, Wiley, 2004
Last Updated
September 10