Research Methods in Psychology I - PSY00015C
Module will run
| Occurrence | Teaching period |
|---|---|
| A | Semester 1 2026-27 |
Module aims
This module will equip you with skills required for the effective study of psychology. Some of these skills are practical ones, such as computer skills, statistical analysis, and presenting results of experiments, whilst others are more conceptual, for example designing high quality studies, interpreting statistical findings, and critically evaluating conclusions of studies you conduct, or those conducted by others. r. Students will gain theoretical understanding of basic statistical concepts and tests as well as experience using statistical packages.
Module learning outcomes
- Demonstrate an understanding of the basic concepts in experimental design
- Demonstrate an understanding of the importance and relevance of data analysis in experimental psychology
- Demonstrate and understanding of different types of experiment, data and tests used in experimental psychology
- Describe and evaluate qualitative methods
- Be able to independently conduct content analysis
- Show proficiency in using a statistical package to compute: summary statistics; z-scores; chi square; binomial tests; parametric and non-parametric comparisons of two means (between and within subjects) and correlations
- Be able to select and provide a rationale for using a statistical test to analyse a particular datasets
- Present results from statistical tests correctly either in text, tables, or figures
Module content
We are aware that statistics is an area many students feel nervous about: we do not assume any maths knowledge above GCSE level and we aim to support all our students to graduate happy and confident dealing with data. We begin with an introduction to research design and statistics, including different data types, descriptive statistics (e.g. Means, Medians, Standard Deviation etc). We talk about different experimental methods and the pros and cons of each (e.g. within vs between subject design), and learn to consider confounding and extraneous variables when evaluating a study’s conclusions. We then learn about concepts such as normality of distributions, and significance testing. We go on to explore several statistical tests, including t-tests, chi-square, binomial tests, and simple correlations. When learning about the tests, we discuss what the test is used for, how to check our data meet the assumptions for each test, how to run the test on the computer, how to interpret the outputs, what the outputs tell us about our hypotheses, and how to write up the results of the test. We also talk about what to do if the data don’t meet the required assumptions. Lectures cover all the theory needed for your assessment, while computer-lab sessions teach you the skills you need for the rest of the course, allowing you to practice these skills with guidance, to help you gain confidence running the tests you will need elsewhere in the course.
Indicative assessment
| Task | % of module mark |
|---|---|
| Closed/in-person Exam (Centrally scheduled) | 100.0 |
Special assessment rules
None
Indicative reassessment
| Task | % of module mark |
|---|---|
| Closed/in-person Exam (Centrally scheduled) | 100.0 |
Module feedback
The marks on all assessed work will be provided on e-vision.
Indicative reading
We have a custom made textbook to support key study skills throughout your degree: Slocombe, Katie (2010). All you ever wanted to know about research methods and academic skills. Pearson.
In Year 1 we recommend reading about the topics covered in Dancey, Christine P. (2007). Statistics without maths for psychology. Pearson Prentice Hall, as a gentle introduction to statistics used in Psychology.