SHE Level 2
SCQF Credit Points 20.00
ECTS Credit Points 10.00
Module Code M2C825411
Module Leader Kareena McAloney-Kocaman
School School of Health and Life Sciences
Subject Psychology
  • A (September start)

Pre-Requisite Knowledge

Philosophy and Methods, Data Management [or equivalent introductory research methods module/class].

Summary of Content

This module provides students with the opportunity to develop foundational data analysis skills that are key to carrying out research in psychology. These skills include using knowledge of hypothesis testing and appropriate software to analyse data and interpret output, an introduction to quantitative inferential statistical tests (e.g. selecting statistical tests, tests of difference and correlation/association, Oneway and 2-way ANOVA) and qualitative methods and analysis (e.g. Thematic Analysis). Teaching is via practical labs, with face-to-face lectures and online materials to inform, support, and supplement student learning.


The aim of this module is to provide students with basic skills in data analysis that will build on Research Methods Modules in Level 1, and will provide a foundation for Research Methods teaching in Level 3, as well as the Level 4 Empirical Project. There are three main strands to the teaching 1) introduction to inferential quantitative data analysis 2) introduction to qualitative data analysis 3) practical application of knowledge e.g. selecting statistical tests, analysing quantitative and qualitative data, interpreting data output, reporting data analysis. There is an emphasis on the acquisition of practical skills in relation to data analysis, including use of appropriate software.

Learning Outcomes

On successful completion of this module, the student should be able to:1. Apply knowledge of hypothesis testing to practical data analysis (assessed by practical)2. Perform inferential statistical analysis of quantitative data (assessed by practical)3. Perform qualitative analysis (assessed by qualitative coursework)4. Apply inferential statistical knowledge to the interpretation of quantitative data (assessed by practical)5. Present qualitative data (assessed by qualitative coursework)6. Present quantitative data (assessed by practical)

Teaching / Learning Strategy

Teaching will be delivered via weekly practical labs (38 hours across the trimester) and face-to-face lectures (6 hours across the trimester). Independent learning will be facilitated by asking students to prepare for practical labs and coursework. Formative assessment (e.g. lab exercises) will provide experience in interpreting and reporting quantitative inferential data as well as qualitative data.

Indicative Reading

Brace, N., Kemp., R. Snelgar, R. (2012) SPSS for psychologists 5 th edition Basingstoke: Palgrave MacMillan Braun, V. & Clarke, V. (2013) Successful qualitative research; a practical guide for beginners . London: Sage Dancey, C. & Reidy, J. (2017). Statistics Without Maths for Psychology . Harlow: Pearson Education Ltd.

Transferrable Skills

-360 1. Be able to select an appropriate statistical test, perform analysis, interpret this analysis, and report the results according to recognised convention. -360 2. Be able to produce an individual piece of work that will aid future academic performance (e.g. Empirical Project) -360 3. Digital capability skills -360 4. Ability to effectively utilise data analysis computer package

Module Structure

Activity Total Hours
Lectures (FT) 6.00
Assessment (FT) 40.00
Practicals (FT) 38.00
Independent Learning (FT) 116.00

Assessment Methods

Component Duration Weighting Threshold Description
Coursework 1 n/a 70.00 35% Individual Practical Quantitative Assessment
Coursework 2 n/a 30.00 35% Individual Qualitative Coursework (1500 words)