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PSY-40103 - Module Specification
School of Psychology
Faculty of Natural Sciences

For academic year: 2024/25 Last Updated: 22 November 2024

PSY-40103 - Advanced Computational and Statistical Approaches to Behaviour
Coordinator: Chris Street Tel: +44 1782 7 33386
Lecture Time: See Timetable...
Level: Level 7
Credits: 15
Study Hours: 150
School Office: 01782 733736

Programme/Approved Electives for 2024/25

None

Available as a Free Standing Elective

No

Co-requisites

None

Prerequisites

None

Barred Combinations

None

Description for 2024/25

Understanding behaviour is challenging because of the complexity of the mind, a wide range of situational and social influences on it, and individual differences amongst people. Researchers tackle this complexity using a variety of computational and statistical approaches. This module will provide you with a grounding in a selection of advanced quantitative methods, leaving you with a rich and integrated understanding of how computational and statistical methods can be used to predict behaviour and test scientific theories. Indicative topics include machine learning, cognitive modelling, Bayesian analysis, and agent-based modelling.

Aims
This module will introduce students to various advanced computational and statistical approaches to understanding behaviour. The module will provide students with a solid understanding of these approaches, and students will critically engage with how these approaches have been utilised to address a research question of interest to the student.

Intended Learning Outcomes

Handle and prepare research data for use with advanced computational and statistical approaches to understanding behaviour
: 1,2
Deploy a variety of advanced computational and statistical approaches to understanding behaviour: 1,2
Interpret the results of advanced computational and statistical approaches to understanding behaviour: 1,2
Critically evaluate competing cognitive theoretical perspectives using advanced computational techniques: 2
Communicate a research project for a scientific audience: 2

Study hours

- 24 hours of scheduled synchronous teaching (interactive, discussion-based etc.)
- 24 hours of preparation for upcoming teaching sessions
- 12 hours of guided asynchronous learning
- 90 hours preparing for and completing assessments

School Rules

None

Description of Module Assessment

1: Class Test weighted 30%
Analytical Practical


2: Laboratory Report weighted 70%
3000 word cognitive modelling lab report


The University undertakes a continuous review of its teaching and research provision to ensure programmes are of a high quality and changes may be made to modules where it is necessary and reasonable to do so. Please be aware that minor changes to modules, such as a change to an individual assessment, can occur up until enrolment, although we endeavour to give you as much notice as possible of any changes. Details about the circumstance in which changes are made to programmes can be found in the Student Agreement, available at: https://www.keele.ac.uk/legalgovernancecompliance/governance/actcharterstatutesordinancesandregulations/studenttermsconditions/

Last Updated: 22 November 2024