SO491 Half Unit
Quantitative Social Research Methods
This information is for the 2019/20 session.
Dr Ioanna Gouseti STC.S105a
This course is available on the MPhil/PhD in Cities Programme, MPhil/PhD in Sociology, MSc in Economy, Risk and Society , MSc in Political Sociology and MSc in Sociology. This course is available with permission as an outside option to students on other programmes where regulations permit.
This course has two main goals. It first introduces students to a range of quantitative methodologies used in contemporary social research. Some of these are widespread, others less so, and the class will be keen to explore a wide variety of them, from experimental and survey methods to linear regression and structural equation modelling. The course’s second goal is to reflect on specific topics of the design of quantitative social research and the analysis of quantitative research data. The specific topics involve the articulation of research interest or question, the choice of appropriate quantitative methods to address research questions, and the key strategies for the analysis of quantitative data. This process is most critical when it comes to crafting powerful sociological arguments and theories that are supported by empirical evidence. Our interest in the design of quantitative research and the analysis of quantitative data will allow students to discuss problems of measurement and sampling, conceptualization, inference, and causality. It will also expose students to important debates and divides in quantitative sociology, such as the one between approaches aiming at the establishment of causality on the one hand, and approaches interested in the analysis of probabilities on the other. To achieve these two goals, we will use a case study approach. For every method we cover, we will read a selection of articles taken from the major generalist journals in the discipline. By analyzing and criticizing the operationalization of quantitative methods in these articles, we will cover issues of research design and get a sense of what each method does (and does not do), of the vision of the social world it conveys, and of the type of questions it can be applied to.
30 hours of workshops in the MT.
Reading Weeks: Students on this course will have a reading week in MT Week 6, in line with departmental policy.
Students must write memos based on course readings and class activities.
Abbott, A. (2004). “Ideas and Puzzles”, Chapter 7 in Methods of Discovery: Heuristics for Social Sciences. New York: Norton, pp. 211-248.
Fox, C. (2004). “The Changing Color of Welfare? How Whites’ Attitudes toward Latinos Influence their Support for Welfare”, American Journal of Sociology 110, 580-625.Legewie, J. (2013). Terrorist Events and Attitudes toward Immigrants: A Natural Experiment. American Journal of Sociology, 118(5), 1199-1245.
Piketty, T., & Saez, E. (2003). Income Inequality in the United States, 1913-1998. The Quarterly Journal of Economics, 118(1), 1-39.
Lim, H., & Duan, H. (2015). Should we blame the graduates for their unemployment? A happiness approach. Hitotsubashi Journal of Economics, 56(2), 243-258.
Salganik, Matthew J., Peter S. Dodds, and Duncan J. Watts. 2006. “Experimental Study of Inequality and Unpredictability in an Artificial Cultural Market”, Science 311: 854–856.
Savage, M., Devine, F., Cunningham, N., Taylor, M., Li, Y., Hjellbrekke, J., . . . Miles, A.(2013). A New Model of Social Class? Findings from the BBC's Great British Class Survey Experiment. Sociology: The Journal of the British Sociological Association, 47(2), 219.
Exam (50%, duration: 2 hours) in the summer exam period.
Memo (25%) and memo (25%) in the MT.
The course is assessed by two 1,500 word memos due in MT Weeks 9 & 11 (50%) and an unseen 2 hour exam (50%).
An electronic copy of the first assessed essay, to be uploaded to Moodle, no later than 4.00pm on the Tuesday of Week 9 of Michaelmas Term.
An electronic copy of the second assessed essay, to be uploaded to Moodle, no later than 4.00pm on the Tuesday of Week 11 of Michaelmas Term.
Attendance at all classes and submission of all set coursework is required.
Total students 2018/19: 23
Average class size 2018/19: 23
Controlled access 2018/19: No
Value: Half Unit
Personal development skills
- Team working
- Problem solving
- Application of information skills
- Specialist skills