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DRPS : Course Catalogue : School of Health in Social Science : Clinical Psychology

Postgraduate Course: Psychological Research Methods: Data Management and Analysis (CLPS11056)

Course Outline
SchoolSchool of Health in Social Science CollegeCollege of Arts, Humanities and Social Sciences
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) AvailabilityAvailable to all students
SCQF Credits20 ECTS Credits10
SummaryThis 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 will be structured around ten workshops comprised of lectures and practical sessions, online activities and supportive materials. It will familiarise students with both quantitative and qualitative analysis, mainly focusing on handling and analysis of quantitative data using SPSS. Both parametric and non-parametric statistics will be covered. The practical sessions will allow students to practise conducting analysis using SPSS (statistics package)

The course is a core component of the MSc Psychology of Mental Health (Conversion) and is not open to students from other programmes.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements None
Information for Visiting Students
High Demand Course? Yes
Course Delivery Information
Academic year 2022/23, Available to all students (SV1) Quota:  200
Course Start Semester 1
Course Start Date 19/09/2022
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 200 ( Lecture Hours 10, Seminar/Tutorial Hours 1.5, Supervised Practical/Workshop/Studio Hours 13.5, Programme Level Learning and Teaching Hours 4, Directed Learning and Independent Learning Hours 171 )
Assessment (Further Info) Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
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%).
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:
  1. Demonstrate knowledge and understanding of the different levels of measurement (including the difference between parametric and non-parametric data), difference between one and two tailed hypotheses and measures of central tendency.
  2. Enter data into SPSS, screen data for errors and perform visual and statistical inspection of distributions and transform data.
  3. Know which statistical tests are most commonly used for answering questions about between and within group differences and relationships between variables, for different levels of measurement.
  4. Conduct statistical analyses to answer questions about differences and relationships between variables, including testing of assumptions, interpretation of the output and post-hoc analyses (using SPSS).
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
KeywordsNot entered
Course organiserDr Melina Kyranides
Tel: (0131 6)51 5148
Course secretaryMs Sarah Paquette
Tel: (0131 6)51 3969
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