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

Tied to	G1K509

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