Skip to main content
 

MATH30220: Decision Theory

It is possible that changes to modules or programmes might need to be made during the academic year, in response to the impact of Covid-19 and/or any further changes in public health advice.

Type Tied
Level 3
Credits 20
Availability Available in 2024/2025
Module Cap None.
Location Durham
Department Mathematical Sciences

Prerequisites

  • Calculus and Probability, Linear Algebra

Corequisites

  • None

Excluded Combinations 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

ActivityNumberFrequencyDurationTotalMonitored
Lectures422 per week for 20 weeks and 2 in term 31 Hour42 
Problems Classes8Four in each of terms 1 and 21 Hour 8 
Preperation and Reading150 
Total200 

Summative Assessment

Component: ExaminationComponent Weighting: 100%
ElementLength / DurationElement WeightingResit Opportunity
Written examination3 Hours100 

Formative Assessment

Eight written or electronic assignments to be assessed and returned. Other assignments are set for self-study and complete solutions are made available to students.

More information

If you have a question about Durham's modular degree programmes, please visit our Help page. If you have a question about modular programmes that is not covered by the Help page, or a query about the on-line Postgraduate Module Handbook, please contact us.

Prospective Students: If you have a query about a specific module or degree programme, please Ask Us.

Current Students: Please contact your department.