Scientific Computing with Matlab
| Code | School | Level | Credits | Semesters |
| PSGY3047 | Psychology | 3 | 10 | Autumn Malaysia |
- Code
- PSGY3047
- School
- Psychology
- Level
- 3
- Credits
- 10
- Semesters
- Autumn Malaysia
Summary
This module will introduce students to the basics of interactive programming and provide solid practical training in Matlab for research purposes. Students will go through a series of lectures supplemented with structured programming exercises (in specified weeks) for reconsolidation, and practicals.
Target Students
BSc Psychology / BSc Psychology and Cognitive Neuroscience students at UNM. The module is aimed at students with little or no previous experience in programming.
Classes
- One 2-hour practicum each week for 2 weeks
- One 2-hour lecture each week for 10 weeks
Details: This module will assess several topics associated with programming skills required for research, such as programming concepts and grammar, image processing (e.g., grayscale conversion, resize, rotation), behavioural experiments (using psychtoolbox), data analysis (including standard statistical tests such as correlations, t-tests and chi-squared tests) and data visualisation. Students will actively participate during lectures to complete short coding exercises and will get sample datasets to work-on outside of class time.
Assessment
- 50% Practical 1: Coding exercise to be completed and submitted during the class.
- 50% Practical 2: Coding exercise to be completed and submitted during the class.
Assessed by end of autumn semester
Educational Aims
To provide students with some basic knowledge and practical training in programming concepts, designing and developing behavioural experiments, data collection, conducting standard statistical tests to analyse small and large-scale data and visualising data using MATLAB.Learning Outcomes
- Knowledge and understanding: Students will familiarise themselves with the basics of programming in Matlab, a programming language widely used by scientists and engineers.
- Knowledge and understanding: Students will learn how to develop psychophysical experiments to cater their research needs using a language that is relatively user-friendly and flexible.
- Intellectual skills: Student will learn problem solving skills from the bug-fixing exercises provided to them
4. Transferable skills: students will learn to apply what they learnt for large- scale data analysis and creative data visualisation in both academic and industrial environments
Conveners
- Dr Ahamed Miflah Hussain Ismail