SO102
Data in Society: Researching Social Life
This information is for the 2023/24 session.
Teacher responsible
Qilyu Hong STC.S114 and Dr Anastasia Kakou COL 8.11
Availability
This course is compulsory on the BSc in Sociology. This course is not available as an outside option nor to General Course students.
Course content
This course explores how numbers are deployed in social settings, and how they are used in sociology to construct and challenge our understanding of the social world. The first part of the course introduces students to the importance of quantification in modern societies, familiarizes them with the main instruments for the collection of quantitative data, and provides them with an overview of the methods used to treat such data in contemporary sociology. We cover both descriptive and explanatory methods, and we reflect on the vision of the social world implicitly associated with each of the methods we encounter. In the second part students start learning basic descriptive skills of quantitative data analysis, notably how to download large data sets, how to manipulate variables and carry out descriptive statistical analyses with statistical software Stata, and how to present statistical information in tabular and graphical form. The quantitative analysis is done in the context of a sociological observation or hypothesis, and emphasis is given on the interpretation of the results and their comparison to the findings of key readings.
Teaching
This course is delivered through a combination of lectures, online materials and classes totalling a minimum of 40 hours across Autumn Term (AT) and Winter Term (WT).
Reading Weeks: Students on this course will have a reading week in AT Week 6 and WT Week 6, in line with departmental policy.
Formative coursework
One 2000-word essay (AT).
One 1500-word report including a review of key readings, data processing and descriptive statistical analysis using Stata, interpretation of results, and conclusion (WT).
Indicative reading
Desrosières, Alain. 2002. The Politics of Large Numbers: A History of Statistical Reasoning. Cambridge: Harvard University Press.
Savage, Mike, and Roger Burrows. 2007. “The Coming Crisis of Empirical Sociology”, Sociology 41: 885-898.
Field, A. P. (Ed.). (2018). Introduction. In Discovering statistics using IBM SPSS statistics (Fifth edition). Sage Publications. Wheelan, C. (2013). Chapter 11: Regression Analysis- The miracle elixir. In Naked Statistics: Stripping the dread from the data. (p. 29).
Jackson, M., & Cox, D. R. (2013). The Principles of Experimental Design and Their Application in Sociology. Annual Review of Sociology, 39(1), 27–49. https://doi.org/10.1146/annurev-soc-071811-145443
Osborne, T., & Rose, N. (1999). Do the social sciences create phenomena?: The example of public opinion research. The British Journal of Sociology, 50(3), 367–396. https://doi.org/10.1111/j.1468-4446.1999.00367.x
Catherine Marsh and Jane Elliot (2008): Exploring Data (2nd ed.)
Assessment
Project (50%, 3000 words) in the ST.
Take-home assessment (50%) in January.
Take home exam to be completed in the January exam period.
An electronic copy of the assessed project, to be uploaded to Moodle, no later than 4.00pm on the second Thursday of Spring Term.
Attendance at all classes and submission of all set coursework is required.
Key facts
Department: Sociology
Total students 2022/23: 50
Average class size 2022/23: 17
Capped 2022/23: No
Lecture capture used 2022/23: Yes (MT & LT)
Value: One Unit
Course selection videos
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