Postgraduate Course: Psychological Research Methods: Data Management and Analysis (CLPS11056)
Course Outline
| School | School of Health in Social Science |
College | College of Arts, Humanities and Social Sciences |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Available to all students |
| SCQF Credits | 20 |
ECTS Credits | 10 |
| Summary | This option is a core course for the MSc in Psychology of Mental Health (Conversion). It focuses on data analysis. The course will be assessed through a qualitative task and a quantitative task, designed to reveal qualitative analytical skills, statistical skills and understanding of the appropriateness of statistical techniques for different types of data. |
| Course description |
This course aims to provide students with both a theoretical and practical understanding of the use of statistics in psychology. It will familiarise students with both quantitative and qualitative methods, with a primary focus on quantitative methods. Over the course, lectures will cover topics such as t-tests, ANOVA, regression, and thematic analysis, among others. Additionally, students will attend labs during which they gain hands-on practice implementing the content covered in lectures.
The course is a core component of the MSc Psychology of Mental Health (Conversion) and is not open to students from other programmes. The course will run cross the first and second teaching blocks in Semester 1.
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
|
Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
Information for Visiting Students
| Pre-requisites | None |
| High Demand Course? |
Yes |
Course Delivery Information
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| Academic year 2025/26, Available to all students (SV1)
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Quota: 200 |
| Course Start |
Semester 1 |
| Course Start Date |
15/09/2025 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
200
(
Lecture Hours 20,
Seminar/Tutorial Hours 1,
Supervised Practical/Workshop/Studio Hours 10,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
165 )
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| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
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| Additional Information (Assessment) |
There will be three assessments for this course.
First, a formative assessment will take place in the last session of the first semester. This will require the students to enter data into SPSS and complete simple analyses learned so far
There will be two summative assessments for the course:
i) A group report using qualitative analysis (30%).
ii) A structured report using quantitative analyses (70%).
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| Feedback |
The feedback and marks for this course are returned via the Turnitin online submission system. |
| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Describe both qualitative and quantitative data using appropriate methods given data type
- Identify appropriate statistical tests to use to address research aims
- Conduct and interpret a range of statistical tests on quantitative data
- Report results from analyses in alignment with APA standards
- Design and conduct a qualitative analysis, effectively synthesizing findings, demonstrating critical engagement with research methodologies and ethical considerations, overall producing a cohesive qualitative research report.
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Reading List
Field, A. (2017). Discovering statistics using IBM SPSS statistics. (5th ed.). Sage.
Pallant, J. (2020). SPSS survival manual: A step by step guide to data analysis using IBM SPSS. Routledge. |
Additional Information
| Graduate Attributes and Skills |
Develop your research knowledge that will enable you to discuss, share, present and analyse data and information in various formats and from a range of sources
Develop your research methods and data analysis skills
Develop your critical reflection and writing skills |
| Keywords | Not entered |
Contacts
| Course organiser | Dr Monica Truelove-Hill
Tel:
Email: m.truelovehill@ed.ac.uk |
Course secretary | Ms Yuke Duan
Tel:
Email: yduan@ed.ac.uk |
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