Data in Society: Researching Social Life
This information is for the 2020/21 session.
Prof Michael Savage STC.S210 and Dr Anastasia Kakou COL.5.13
This course is compulsory on the BSc in Sociology. This course is available with permission as an outside option to students on other programmes where regulations permit. This course is not available to General Course students.
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.
This course is delivered through a combination of lectures, online materials and classes totalling a minimum of 40 hours across MT and LT, with revision sessions in ST.
Reading Weeks: Students on this course will have a reading week in MT Week 6 and LT Week 6, in line with departmental policy.
One 2000 word essay (MT).
One report including a review of key readings, data processing and descriptive statistical analysis using Stata, interpretation of results, and conclusion (LT).
Gould, Stephen Jay. 1981. The Mismeasure of Man. New York: Norton.
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.
Wasserman, Stanley, et Katherine Faust. 1994. Social Network Analysis: Methods and Applications. Cambridge: Cambridge University Press.
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.
Gelman, Andrew, and Jennifer Hill. 2006. Data Analysis Using Regression and Multilevel/Hierarchical Models. Cambridge: Cambridge University Press.
Catherine Marsh and Jane Elliot (2008): Exploring Data (2nd ed.)
Essay (50%, 3000 words) in the ST.
Take-home assessment (50%) in January.
Take home assessment to be completed during the January exam period.
An electronic copy of the assessed essay, to be uploaded to Moodle, no later than 4.00pm on the second Thursday of Summer Term.
Attendance at all classes and submission of all set coursework is required.
Student performance results
(2017/18 - 2019/20 combined)
|Classification||% of students|
Important information in response to COVID-19
Please note that during 2020/21 academic year some variation to teaching and learning activities may be required to respond to changes in public health advice and/or to account for the situation of students in attendance on campus and those studying online during the early part of the academic year. For assessment, this may involve changes to mode of delivery and/or the format or weighting of assessments. Changes will only be made if required and students will be notified about any changes to teaching or assessment plans at the earliest opportunity.
Total students 2019/20: 40
Average class size 2019/20: 14
Capped 2019/20: No
Value: One Unit