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| Unit name |
Advanced Quantitative Research |
| Unit code |
SOCIM3133 |
| Credit points |
20 |
| Level of study |
M/7
|
| Teaching block(s) |
Teaching Block 2 (weeks 13 - 24)
|
| Unit director |
Professor. Surridge |
| Open unit status |
Not open |
| Pre-requisites |
Quantitative Social Research or equivalent
|
| Co-requisites |
None
|
| School/department |
School of Sociology, Politics and International Studies |
| Faculty |
Faculty of Social Sciences and Law |
Description including Unit Aims
Building on the teaching provided in the unit, Quantitative Social Research, this covers more advanced techniques of quantitative analysis; problems that commonly occur and the various methods of presentation of quantitative material. Specific topics include normal distributions and t-tests; ANOVA; correlation and regression; multivariate linear regression; residuals and interaction; logistic regression; log linear models; factor analysis; the use of comparative datasets; and the writing of quantitative reports.
Aims:
- To familiarise students with aspects of computing most relevant to analysis of quantitative datasets in sociological research
- To make students aware of the range of quantitative social research methods and their appropriateness for specific tasks and research questions
- To provide practical training in data handling and in medium-level and more advanced statistical techniques of multivariate analysis using SPSS for Windows
- To encourage an enquiring and critical approach to data analysis
- To give students a realistic experience of quantitative research based on the analysis of a full secondary dataset
Intended Learning Outcomes
- An awareness of main secondary data sources and the ability to access them
- Capacity to investigate a substantive area of sociological interest using appropriate quantitative tools
- A wareness of shoengths and limitations of data sources and analytical teclmiques
- Ability to utilise data analysis software with proficiency and confidence
- Capacity to evaluate the research practice, data and interpretations of others
- Ability to communicate results of data analYsis both in writiIl& and verbally
Teaching Information
Each week, the session will be introduced by a brief lecture with discussion, followed by hands-on practice on the computer system.
Assessment Information
Students will be assessed by one coursework project at the end of the Semester. This will take the form of a detailed piece of analysis of a survey dataset, equivalent to a 4000 word essay.
Reading and References
- Byrne, D (2002) interpreting Quantitative Data, Sage
- De Vaus, D.A (1996) Surveys in Social Research, UeL Press
- Fielding, J and Gilbert, N (2000) Understanding Social Statistics, Sage
- Grimm, L., & Paul Yarnold Paperback (1998). Reading and Understanding Multivariate Statistics.
- American Psychological Association
- Miller, R., Acton, c., Fullerton, D and Maltby, J. (2002) SPSSfor Social Scientists Palgrave.
