Please note: there may be some adjustments to the teaching arrangements published in the course catalogue for 2020-21. Given current circumstances related to the Covid-19 pandemic it is anticipated that some usual arrangements for teaching on campus will be modified to ensure the safety and wellbeing of students and staff on campus; further adjustments may also be necessary, or beneficial, during the course of the academic year as national requirements relating to management of the pandemic are revised.

Introduction to MatLab Programming (PGT) PSYCH5016

  • Academic Session: 2022-23
  • School: School of Psychology and Neuroscience
  • Credits: 10
  • Level: Level 5 (SCQF level 11)
  • Typically Offered: Semester 2
  • Available to Visiting Students: No
  • Available to Erasmus Students: No

Short Description

This course introduces students to the MatLab environment through hands-on sessions providing a mix of lectures and in class exercises. Students create and manipulate MatLab variables, perform basic computations, use in-built functions, program new functions, program scripts, and produce various graphical representations.



Requirements of Entry

Typically a 2:1 honours degree in psychology or related discipline.

For the MSc Brain Sciences, at least a second class (2:2) honours degree in neuroscience, physiology, psychology or acceptable equivalent(s).


Summative assessment comprises of a series of online assessments available to students following a lecture where the content of each assessment is aligned with the skills and content covered up to and including the just completed class. Students use MatLab to explore a new dataset and answer questions by producing graphical representations, a justification of the methods employed, a description of the results and conclusions.

Main Assessment In: April/May

Course Aims

To introduce students to the MatLab programming environment so that they can start to make scripts to run experiments, create stimuli, explore datasets, and perform statistical analyses.

Intended Learning Outcomes of Course

By the end of the course students will be able to:

■ Critically analyse the workspace, variables, basic mathematical operations, graphs.

■ Critically analyse conditional statements (greater than, less than) scripts.

■ Critically analyse flow control (for loops, if statements), functions.

■ Reflect critically on advanced variables, advanced flow control, file operations.

Minimum Requirement for Award of Credits

Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.