This module runs in Term 1 and is available for students on a course where it is a listed option and as an Unusual Option for students who have taken the pre-requisites.
Pre-requisites:
ST119 Probability 2 OR ST120 Introduction to Probability.
Throughout their history, game and decision theories have used ideas from mathematics and probability to help understand, explain, and direct human behaviour. Questions explored in the module include: What is probability? A set of axioms, a relative amount of outcomes, a belief? And how can this be elicited? What guides decision-making when outcomes are uncertain? What happens when information is only partial or ambiguous? What if there is more than one person, or how are decisions made in games?
Answers will be embedded into theories and illustrated with practical examples from a wide range of applications including engineering, economics, finance, business, sciences, psychology and medicine.
This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.
This module introduces the use of decision theory for making rational decisions in the face of uncertainty
By the end of the module, students should be able to:
Peterson “An introduction to decision theory”. CUP, 2017.
Parmigiani & Inoue “Decision Theory”. Wiley, 2009.
Karlin & Peres “Game Theory, Alive”. AMS, 2016.
View reading list on Talis Aspire
Demonstrate knowledge of key mathematical and statistical concepts, both explicitly and by applying them to the solution of mathematical problems.
Create structured and coherent arguments communicating them in written form.
Analyse problems, abstracting their essential information formulating them using appropriate mathematical language to facilitate their solution.
Written communication skills: Students complete written assessments that require precise and unambiguous communication in the manner and style expected in mathematical sciences.
Verbal communication skills: Students are encouraged to discuss and debate formative assessment and lecture material within small-group tutorials sessions. Students can continually discuss specific aspects of the module with the module leader. This is facilitated by statistics staff office hours.
Problem-solving skills: The module requires students to solve problems with complex solutions and this requirement is embedded in the module’s assessment.
| Type | Required | Optional |
|---|---|---|
| Lectures | 20 sessions of 1 hour (17%) | 2 sessions of 1 hour |
| Private study | 78 hours (68%) | |
| Assessment | 17 hours (15%) | |
| Total | 115 hours |
Weekly revision of lecture notes and materials, wider reading, working on practice exercises and preparing for examination.
No further costs have been identified for this module.
You must pass all assessment components to pass the module.
| Weighting | Study time | Eligible for self-certification | |
|---|---|---|---|
| Computer-based assessments | 10% | 15 hours | No |
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A set of small computer based assessments which will take place during the term that the module is delivered. |
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| In-Person Examination | 90% | 2 hours | No |
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You will be required to answer all questions on this examination paper.
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| Weighting | Study time | Eligible for self-certification | |
|---|---|---|---|
| Games and Decisions examination | 100% | No | |
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You will be required to answer all questions on this examination paper.
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Computer-based assessment provides immediate feedback after the submission deadline.
Cohort-level feedback will be available on the exam.
Students are actively encouraged to make use of office hours to build up their understanding, and to view all their interactions with lecturers and class tutors as feedback.
This module is Option list A for:
This module is Option list B for: