Applied Quantitative Data Analysis
| Module title | Applied Quantitative Data Analysis |
|---|---|
| Module code | POLM809 |
| Academic year | 2023/4 |
| Credits | 15 |
| Module staff | Dr Andrei Zhirnov (Convenor) |
| Duration: Term | 1 | 2 | 3 |
|---|---|---|---|
| Duration: Weeks | 11 |
| Number students taking module (anticipated) | 20 |
|---|
Module description
The purpose of the course is to improve your quantitative skills and to stimulate interest in quantitative methods across humanities and social sciences. A basic understanding of data collection, analysis and interpretation is essential for contemporary research in many disciplines, both to enable researchers to make direct use of these techniques in their own research and for meaningfully engaging with work that uses these approaches. The module prepares you to read and understand research on topics that involve quantitative evidence and conduct basic data analysis. This module complements the closely linked modules on research methods training (POLM140 and SOCM020) and is alternative to POLM086.
Module aims - intentions of the module
POLM809 intends to provide an applied introduction into quantitative methods in the social sciences. You will acquire skills to understand the use of quantitative tools and techniques and gain hands-on experience with such data analysis tools as Microsoft Excel. You will learn the strengths and weaknesses of various techniques and be taught how to select among various quantitative tools. Examples will be drawn from the humanities and social sciences.
Intended Learning Outcomes (ILOs)
ILO: Module-specific skills
On successfully completing the module you will be able to...
- 1. recognize and evaluate in writing the diversity of specialized techniques and approaches involved in analysing research information, both quantitative and qualitative;
- 2. critically evaluate in writing the issues involved in application of research design in the context of the social sciences;
- 3. Demonstrate acquired skills in data analysis
- 4. demonstrate acquired skills in a computer package for statistical analysis (e.g. SPSS, Stata);
- 5. Show ability to present analysed data in a coherent and effective manner.
ILO: Discipline-specific skills
On successfully completing the module you will be able to...
- 6. demonstrate understanding in the use of advanced tools and techniques of quantitative research;
- 7. examine relationships between complex theoretical concepts with real world, empirical data;
ILO: Personal and key skills
On successfully completing the module you will be able to...
- 8. demonstrate an advanced ability to study independently and effectively;
- 9. communicate effectively in speech and writing;
- 10. use IT for the retrieval and the presentation of a wide variety of information.
Syllabus plan
Whilst the module’s precise content may vary from year to year, it is envisaged that the syllabus will cover some or all of the following topics:
Topic 1: Introduction: why use quantitative data and
Topic 2: Inferential statistics, a primer
Topic 3: Collecting data, sampling, data management and data integrity
Topic 4: Describing data and dealing with missing data
Topic 5: Testing relationships between variables
Topic 6: Visual displays of data
Topic 7: Multivariate statistics
Learning activities and teaching methods (given in hours of study time)
| Scheduled Learning and Teaching Activities | Guided independent study | Placement / study abroad |
|---|---|---|
| 22 | 128 | 0 |
Details of learning activities and teaching methods
| Category | Hours of study time | Description |
|---|---|---|
| Scheduled Learning and Teaching Activities | 22 | 7 weekly two-hour sessions (including introductory session). |
| Guided independent study | 66 | Reading, thinking and preparing for weekly sessions |
| Guided Independent Study | 62 | Web-based learning; Preparation and completion of assessments |
Formative assessment
| Form of assessment | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|
| Final essay outline | 300 words | 1, 2, 6-10 | Written |
Summative assessment (% of credit)
| Coursework | Written exams | Practical exams |
|---|---|---|
| 100 | 0 | 0 |
Details of summative assessment
| Form of assessment | % of credit | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|---|
| 3 practical assignments (written), with exercises focusing on data analysis, visualization and interpretation | 60 | 500 words each (25% each) | 3-10 | Written feedback |
| Final assignment (written): Essay critiquing an approach taken by a published quantitative research paper | 40 | 1500 words | 1, 2, 6-10 | Written feedback |
| 0 |
Details of re-assessment (where required by referral or deferral)
| Original form of assessment | Form of re-assessment | ILOs re-assessed | Timescale for re-assessment |
|---|---|---|---|
| 3 practical assignments (written), with exercises focusing on data analysis, visualization and interpretation (500 words each) | 3 practical assignments (written), with exercises focusing on data analysis, visualization and interpretation (500 words each) | 3-10 | Referral/Deferral period |
| Final assignment (written): Essay critiquing an approach taken by a published quantitative research paper (1500 words) | Final assignment (written): Essay critiquing an approach taken by a published quantitative research paper (1500 words) | 1-2, 6-10 | Referral/Deferral period |
Indicative learning resources - Basic reading
Hudson, Pat. 2000. History by Numbers: An Introduction to Quantitative Approaches. London: Bloomsbury.
Indicative learning resources - Web based and electronic resources
Diamond, Ian, and Julie Jefferies. 2001. Beginning Statistics. SAGE Research Methods (available via UoE library at https://methods.sagepub.com/book/beginning-statistics).
Feinstein, Charles H., and Mark Thomas. 2002. Making History Count: A Primer in Quantitative Methods for Historians. Cambridge: Cambridge University Press (available via UoE library at https://uoelibrary.idm.oclc.org/login?url=http://dx.doi.org/10.1017/CBO9781139164832).
Creswell, John W., and J. David Creswell. 2018. Research Design: Qualitative, Quantitative, and Mixed Methods Approaches. Los Angeles: SAGE (available via UoE library at https://app.kortext.com/borrow/254557).
Pollock III, Philip H. 2020. The Essentials of Political Analysis (3rd ed.). Washington, DC: Congressional Quarterly Press (available via UoE library at https://app.kortext.com/borrow/607045).
Hoover, Kenneth, and Todd Donovan. 2013. The Elements of Social Scientific Thinking. Cengage Learning (available via UoE library at https://www.vlebooks.com/Product/Index/496466).
Additional resources available on ELE – http://vle.exeter.ac.uk/
| Credit value | 15 |
|---|---|
| Module ECTS | 7.5 |
| Module pre-requisites | None |
| Module co-requisites | None |
| NQF level (module) | 7 |
| Available as distance learning? | No |
| Origin date | 01/10/2008 |
| Last revision date | 28/03/2023 |
