Module manager: Dr. Albert Varela
Email: a.varela@leeds.ac.uk
Taught: Semester 1 (Sep to Jan) View Timetable
Year running 2025/26
Students who have not taken SLSP2011 or equivalent should approach the module leader in advance of enrolment to discuss whether prior exposure/knowledge in this area is appropriate for this module.
| SLSP2011 | Sociology and Social Policy Research Methods |
SLSP3065 Quantitative Social Research
This module is not approved as a discovery module
This module will offer students the opportunity to develop fundamental data analytical skills necessary to conduct quantitative social research. It will introduce students to fundamental techniques in exploratory data analysis and modelling as part of a coherent framework that helps them structure and conduct independently a quantitative research project, from inception to reporting. The focus of the module is eminently applied and based on teaching and learning activities that emphasise hands-on work with widely used social research datasets on topics of interest to sociology, social policy, criminology and the wider social sciences. This module is aimed at students wanting to undertake quantitative dissertations in social science degrees and/or students wanting to develop the key skills to conduct applied quantitative research in academic and industry settings after graduation.
This research-based module enables students to develop the skills to analyse quantitative data in order to answer a research question of their choice.
Over the duration of the module students will:
- familiarise themselves with a variety of existing datasets with which to explore their research question.
- develop the ability to import, manipulate and prepare data for analysis to answer substantive research questions using statistical software.
- learn both the substantive and practical considerations involved in analysing data.
- follow a coherent quantitative research workflow that includes data retrieval and preparation, exploratory data analysis and visualisation, statistical modelling, and reporting.
- reflect substantively and methodologically about the strengths and weaknesses of quantitative data analysis in social research.
On successful completion of the module students will have demonstrated the following learning outcomes relevant to the subject:
1. Demonstrate command of standard tools for quantitative social research, such as exploratory data analysis, data visualisation, linear and logistic regression.
2. Identify the appropriate methods to analyse different types of data and evaluate their strengths and limitations in both their own analysis and published research.
3. Evidence their ability to prepare, analyse and interpret quantitative data to answer substantive research questions using statistical software.
4. Effectively present and report findings from quantitative data analysis using graphs and tables in a clear and systematic way to meet the needs of different types of audiences.
Skills Learning Outcomes
On successful completion of the module students will have demonstrated the following skills learning outcomes:
1. Problem solving and analytical skills: students will take a logical approach to solving problems; resolving issues by tackling from different angles, using both analytical and creative skills. The ability to understand, interpret, analyse and manipulate numerical data.
2. Core literacies – students will be able to understand, interpret, analyse and manipulate numerical data.
3. Communication – students will be clear, concise and focused; being able to tailor message for the audience and listening to the views of others.
4. Digital proficiency and productivity: - students will be able to select, use, troubleshoot and adapt digital devices, networks, applications and services to achieve specific goals.
Details of the syllabus will be provided on the Minerva organisation (or equivalent) for the module
| Delivery type | Number | Length hours | Student hours |
|---|---|---|---|
| Practical | 2 | 1 | 2 |
| Practical | 5 | 2 | 10 |
| Practical | 11 | 2 | 22 |
| Independent online learning hours | 11 | ||
| Private study hours | 155 | ||
| Total Contact hours | 34 | ||
| Total hours (100hr per 10 credits) | 200 | ||
A formal formative assessment opportunity will be provided for each summative assessment task, which is specifically pedagogically aligned to that task. As part of this, each student will receive feedback designed to support the development of knowledge and skills that will be later assessed in the summative task.
| Assessment type | Notes | % of formal assessment |
|---|---|---|
| Coursework | . | 90 |
| Coursework | . | 10 |
| Total percentage (Assessment Coursework) | 100 | |
Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated
Check the module area in Minerva for your reading list
Last updated: 15/05/2025
Errors, omissions, failed links etc should be notified to the Catalogue Team