MAS3908 : Experimental Design
- Offered for Year: 2018/19
- Module Leader(s): Professor John Matthews
- Owning School: Mathematics, Statistics and Physics
- Teaching Location: Newcastle City Campus
|Semester 2 Credit Value:||10|
To introduce students to the idea that statistical thinking is not confined to the analysis of data but is vital to the way that scientific and other experiments are planned.
It is well-known that experiments underpin much laboratory science and medicine, where clinical trials are a form of experiment involving human subjects. The approach is also used in areas less readily associated with experiments: industrial process industries have used them for many years and many web-based activities are just starting to exploit the experimental method. While the use of experiments is widely appreciated, the range and potential of different types of design, and their correct analysis, is not as widely disseminated. The course will describe the basic ideas of statistical design and introduce some of the more commonly used designs, together with the appropriate methods of analysis.
Outline Of Syllabus
Idea and role of randomization in treatment estimation, including use in clinical trials. Role of sample size in experimentation and sample size calculations (two group case only). Methods of randomization and the role of Bayesian ideas.
Potential confounding factors and use of blocking and randomization to allow for them. Need for correct analysis. Randomized block designs and their analysis, using matrix formulation and link with ANOVA. The idea of efficiency. More complex blocking patterns, including Latin squares and incomplete blocks. Treatment structures such as factorial designs.
Use of experiments in an industrial context and the use of D-optimality.
|Guided Independent Study||Assessment preparation and completion||1||13:00||13:00||Revision for unseen exam|
|Guided Independent Study||Assessment preparation and completion||1||2:00||2:00||Unseen exam|
|Scheduled Learning And Teaching Activities||Lecture||3||1:00||3:00||Problem classes|
|Scheduled Learning And Teaching Activities||Lecture||2||1:00||2:00||Revision lectures|
|Scheduled Learning And Teaching Activities||Lecture||25||1:00||25:00||Formal lectures|
|Scheduled Learning And Teaching Activities||Lecture||1||1:00||1:00||Class test|
|Guided Independent Study||Independent study||1||12:00||12:00||Preparation for class test|
|Guided Independent Study||Independent study||2||6:00||12:00||Preparation for written assignments|
|Guided Independent Study||Independent study||1||21:00||21:00||Studying, practising and gaining understanding of course material|
|Guided Independent Study||Independent study||3||3:00||9:00||Review of written assignments and class test|
Teaching Rationale And Relationship
Lectures are used for the delivery of theory and explanation of methods, illustrated with examples, and for giving general feedback on marked work. Problem Classes are used to help develop the students’ abilities at applying the theory to solving problems. Tutorials are used to identify and resolve specific queries raised by students and to allow students to receive individual feedback on marked work. In addition, office hours (two per week) will provide an opportunity for more direct contact between individual students and the lecturer.
The format of resits will be determined by the Board of Examiners
|Written Examination||40||2||M||5||Class test|
|Prob solv exercises||2||M||5||Two written assignments|
Assessment Rationale And Relationship
A substantial formal unseen examination is appropriate for the assessment of the material in this module. The assignments are expected to consist of two assignments of equal weight: the exact nature of assessment will be explained at the start of the module. The exercises and the class test allow the students to develop their problem solving techniques, to practise the methods learnt in the module, to assess their progress and to receive feedback; these are thus formative as well as summative assessments.