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Tyrone Curtis
Programme Coordinator

Methods Summer Programme
London School of Economics
Houghton Street
London WC2A 2AE

Email: summer.methods@lse.ac.uk|
Tel: +44 (0)20 3199 5379

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Multiple Correspondence Analysis for the Social Sciences


This course offers an introduction to MCA, which is a method that allows researchers to observe the patterning of complex data sets through representing categorical variables as points in N-dimensional space. Although it was developed from the later 1960s, MCA has not previously had a large Anglophone following, but it is an increasingly popular method because of (a) its association with Pierre Bourdieu’s high profile sociology, (b) its capacity to lend itself to visualisation of clusters and (c) its potential for mixed methods research.

This course is suitable for:

  • PhD students, post-doctoral fellows and academic staff in the social sciences, interested in one of the main methods for the clustering of categorical data
  • those interested in learning about the methods used by Pierre Bourdieu for the analysis of cultural fields and social relations
  • market researchers, other commercial researchers, and public sector professionals wishing to learn MCA as a means of clustering complex data sets, and presenting attractive and intuitive visualisations.

Course Benefits
This course will provide students with:

  • a comprehensive introduction to MCA
  • training in how to use SPAD software
  • awareness of key exemplars in social science using MCA and an awareness of the theoretical principles it draws upon.

No statistical knowledge is necessary, but it will be advantageous. Applicants must be at PhD level or higher.

This course will offer a comprehensive introduction to the principles of multiple correspondence analysis. Comprehensive training is also provided in using SPAD software, the most accessible and flexible package to use when carrying out MCA.

Issues covered include mathematical principles of geometric data analysis, the difference between the active space of modalities and the use of supplementary variables, coding issues, working with the cloud of modalities and the cloud of individuals, clustering methods within MCA, and the use of inferential statistics within MCA.

The course is designed to allow the beginner to grasp basic mathematical principles of geometric data analysis. The course will be delivered by a series of lectures by leading international experts in MCA in the morning, with practical sessions in a computer lab in the afternoons.

Teaching Schedule
The following teaching schedule is indicative only, and is subject to change.

Week 1
  Monday   Tuesday Wednesday  Thursday  Friday 
Lecture topic
Introduction to MCA and SPAD Creating and refining active spaces and using supplementary variables Clustering within SPAD Inferential statistics and MCA Exemplars and MCA

Assessment is in the form of a practical assignment completed over the week of the course.

Main Text
Brigitte Le Roux and Henry Rouanet (2010) Multiple Correspondence Analysis. QASS nº 163. SAGE.



Course details

To be confirmed

Lectures, practical classes

New Academic Building, LSE

Teaching faculty
Professor Johs Hjellbrekke| 
University of Bergen
Professor Mike Savage|
Dr Daniel Laurison|
Department of Sociology, LSE

Tuition fees
Student rate: £935
Academic staff/charity rate: £1,250
Professional rate: £1,575


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