Quantitative and Qualitative Methods (C8300)
Quantitative and Qualitative Methods
Module C8300
Module details for 2023/24.
15 credits
FHEQ Level 5
Full Module Description
This module complements the term 1 module 'Discovering Statistics'. It has three components: (a) advanced statistical analysis for various linear models and questionnaire construction and interpretation; (b) observational methods; (c) qualitative data-gathering and analysis. There is one assessed empirical report using some of these techniques, which will enable students to develop skills in research design, data-gathering and analysis and which will therefore equip students for their empirical research projects. There is also an assessed problem set that gives students the opportunity to develop their critical thinking around validity and operationalisation. The statistical analysis parts of the module build upon existing knowledge of statistical theory (in term 1 module). Practical workshops complement the lectures by providing hands-on experience and guidance in using the methods and through small group work on relevant tasks, and encourage consistent development of statistical skills and critical thinking through weekly quizzes.
This module builds on knowledge gained in the core psychology modules C8511: Psychology as a science; C8891: Analysing data; and C8552 Discovering Statistics. Students who are not enrolled on the BSc Psychology course at Sussex are expected to be familiar with the material covered in these modules.
Module Outline
This module complements the term 1 module 'Discovering Statistics'. It has three components: (a) advanced statistical analysis for various linear models and questionnaire construction and interpretation; (b) observational methods; (c) qualitative data-gathering and analysis. There is one assessed empirical report using some of these techniques, which will enable students to develop skills in research design, data-gathering and analysis and which will therefore equip students for their empirical research projects. There is also an assessed problem set that gives students the opportunity to develop their critical thinking around validity and operationalisation. The statistical analysis parts of the module build upon existing knowledge of statistical theory (in term 1 module). Practical workshops complement the lectures by providing hands-on experience and guidance in using the methods and through small group work on relevant tasks, and encourage consistent development of statistical skills and critical thinking through weekly quizzes.
This module builds on knowledge gained in the core psychology modules C8511: Psychology as a science; C8891: Analysing data; and C8552 Discovering Statistics. Students who are not enrolled on the BSc Psychology course at Sussex are expected to be familiar with the material covered in these modules.
Module learning outcomes
Critically understand the theory and application of a range of quantitative statistical models.
Critically understand the principles and practice of observational methods, such as sampling issues, coding, and inter-rater reliability estimates
Understand the limits of several research methods, such as interviewing, thematic analysis and discourse analysis
Initiate critical analysis of research methodologies applied to psychological questions
| Type | Timing | Weighting |
|---|---|---|
| Coursework | 50.00% | |
| Coursework components. Weighted as shown below. | ||
| Report | T2 Week 9 | 50.00% |
| Computer Based Exam | T2 Week 11 | 40.00% |
| Portfolio | T2 Week 11 (2 hours 30 minutes) | 10.00% |
| Computer Based Exam | Semester 2 Assessment | 50.00% |
Timing
Submission deadlines may vary for different types of assignment/groups of students.
Weighting
Coursework components (if listed) total 100% of the overall coursework weighting value.
| Term | Method | Duration | Week pattern |
|---|---|---|---|
| Spring Semester | Lecture | 1 hour | 22222222221 |
| Spring Semester | Practical | 2 hours | 01111111111 |
How to read the week pattern
The numbers indicate the weeks of the term and how many events take place each week.
Dr Vlad Costin
Assess convenor, Convenor
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