Skip to main content Skip to navigation

Module Outlines

EITHER:
Methods and Analysis in Behavioural Science
Behavioural scientists need to excel in the statistical analysis of experimental data and of large data sets, and the module covers these topics. The module also provides an introduction to mathematical modelling of behaviour.
OR:
Advanced qualitative and quantitative analysis

The main aim of this module is to develop an understanding and ability to apply and critically evaluate a variety of standard and advanced methods of both qualitative and quantitative data analysis.

PLUS 1 or 2 options from:
Practical research skills for psychology

The main aim of this module is to develop students’ practical skills in the area of psychological research with an emphasis on using technology and advanced techniques to study and analyse human behaviour and performance. The module includes a theoretical background covering when and why these techniques should be used for studying human behaviour and conducting psychological research. The main themes are computer programming for designing and analyzing experiments, eye movement measurement and analysis, and ERP imaging techniques.

Communication, dissemination, and professional issues

Media awareness is a particularly important component of this training in view of the emphasis on the public understanding of science. This course develops skills in both oral and written presentation based around the topic of psychology. A further aim is to offer guidance to those intending to pursue an academic career in teaching and research within psychology, covering the funding, management, and exploitation of research, and general issues in career development.

Computational modelling

This course introduces students to computational modelling techniques using high-level programming languages (MATLAB). Model fitting and model comparison techniques are covered in detail within the context of understanding human behaviour. A range of model architectures is examined, including mathematical models of memory; connectionist models of language, and exemplar models of categorization and identification. An emphasis is placed on the relation between theory and data and on developing the ability to formulate and construct models.

OR and appropriate module from our undergraduate provision.