Postgraduate Programme and Module Handbook 2020-2021 (archived)
Module MATH30220: Decision Theory
Department: Mathematical Sciences
MATH30220: Decision Theory
| Type | Tied | Level | 3 | Credits | 20 | Availability | Available in 2020/21 | Module Cap | None. |
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| Tied to | G1K509 |
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Prerequisites
- Calculus and Probability, Linear Algebra
Corequisites
- None
Excluded Combination of Modules
- None
Aims
- To describe the basic ingredients of decision theory, for individuals and for groups, and to apply the theory to a variety of interesting and important problems.
Content
- Introduction to decision analysis: utility.
- Uncertainty.
- Statistical decision theory: Bayes decisions.
- Bargaining.
- Game theory.
- Influence diagrams, group decisions and social choice.
Learning Outcomes
Subject-specific Knowledge:
- By the end of the module students will: be able to solve novel and/or complex problems in Decision Theory.
- have a systematic and coherent understanding of theoretical mathematics in the field of Decision Theory.
- have acquired coherent body of knowledge of these subjects demonstrated through one or more of the following topic areas: Formulating decision problems and solving decision trees.
- Utility, value of money, multi-attribute utility.
- Use of data in decision making, statistical decision theory.
- Sequential decision making.
- Game theory, including two-person zero-sum games.
- Bargaining, including Nash' theory.
- Group decisions and social choice.
Subject-specific Skills:
- In addition students will have specialised mathematical skills in the following areas which can be used with minimal guidance: Modelling.
Key Skills:
Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module
- Lectures demonstrate what is required to be learned and the application of the theory to practical examples.
- Assignments for self-study develop problem-solving skills and enable students to test and develop their knowledge and understanding.
- Formatively assessed assignments provide practice in the application of logic and high level of rigour as well as feedback for the students and the lecturer on students' progress.
- The end-of-year examination assesses the knowledge acquired and the ability to solve complex and specialised problems.
Teaching Methods and Learning Hours
| Activity | Number | Frequency | Duration | Total/Hours | |
|---|---|---|---|---|---|
| Lectures | 42 | 2 per week for 20 weeks and 2 in term 3 | 1 Hour | 42 | |
| Problems Classes | 8 | Four in each of terms 1 and 2 | 1 Hour | 8 | |
| Preperation and Reading | 150 | ||||
| Total | 200 |
Summative Assessment
| Component: Examination | Component Weighting: 90% | ||
|---|---|---|---|
| Element | Length / duration | Element Weighting | Resit Opportunity |
| Written examination | 3 Hours | 100% | |
| Component: Continuous Assessment | Component Weighting: 10% | ||
| Element | Length / duration | Element Weighting | Resit Opportunity |
| Eight written assignments to be assessed and returned. Other assignments are set for self-study and complete solutions are made available to students. | 100% | ||
Formative Assessment:
■ Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University