Data in Society: Researching Social Life

This information is for the 2022/23 session.

Teacher responsible

Dr Anastasia Kakou COL.5.13 and Dr Yazmin Morlet Corti STC S114


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.


This course is delivered through a combination of lectures, online materials and classes totalling a minimum of 40 hours across MT and LT.

Reading Weeks: Students on this course will have a reading week in MT Week 6 and LT Week 6, in line with departmental policy.

Formative coursework

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).

Indicative reading

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

(2019/20 - 2021/22 combined)

Classification % of students
First 37.6
2:1 41.9
2:2 16.1
Third 2.2
Fail 2.2

Key facts

Department: Sociology

Total students 2021/22: 55

Average class size 2021/22: 16

Capped 2021/22: No

Lecture capture used 2021/22: Yes (MT)

Value: One Unit

Guidelines for interpreting course guide information

Course selection videos

Some departments have produced short videos to introduce their courses. Please refer to the course selection videos index page for further information.