UE221 - Simple and multiple correspondence analysis

Type d'UE
Méthodologie
Disciplines
Économie, Méthodes et techniques des sciences sociales, Sociologie
Page web
-
Langues
anglais
Mots-clés
-
Aires culturelles
-

In the social sciences, multiple correspondence analysis (MCA) is a statistical technique that perhaps has become best known through the work of the late Pierre Bourdieu (1930-2002), in particular “Distinction” (Bourdieu 1984), “Homo Academicus” (Bourdieu 1988) and “The State Nobility” (Bourdieu 1996). In more recent years, the technique has found a wider audience, and is now used by social scientists in several disciplines.

As a counterpart to principal component analysis (PCA), a geometric technique for the analysis of metric variables, MCA is a geometric technique for the analysis of categorical or categorized variables. Originating in the early 1960s and the French statistician Jean-Paul Benzécri’s work in mathematical linguistics, MCA represents and models data sets as clouds of points in a multidimensional Euclidean space. The interpretation of the data is based on these clouds of points. By combining MCA with inferential techniques and variance analysis, we arrive at an integrated framework of interpretation that also is known under the name of Geometric Data Analysis (GDA).

In a combination of lectures and laboratory exercises, this course will introduce students to the fundamental properties, procedures and rules of interpretation of the most commonly used forms of correspondence analysis, i.e. simple correspondence analysis (CA) and MCA, and also to the most commonly used software. A main emphasis will be put on how to use MCA in one’s own work, and on practical examples and applications. Particular attention will therefore be paid to how MCA can be used in the construction of social spaces.

Le programme détaillé n'est pas disponible.

  • Institutions, organisations, économie et société – M1/S2-M2/S4
    Suivi et validation – semestriel quotidienne = 3 ECTS
    MCC – contrôle continu
  • Johannes Hjellbrekke [référent·e]   professeur des universités, Université de Bergen, Norvège /
Contacts additionnels
-
Informations pratiques
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Direction de travaux des étudiants
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Réception des candidats
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Pré-requis
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  • Université Paris Dauphine

    les 24, 25 et 26 mars 2021, 09:00-18:00


Intervenant·e·s


  • Johannes Hjellbrekke [référent·e]   professeur des universités, Université de Bergen, Norvège /

Planning


  • Université Paris Dauphine

    les 24, 25 et 26 mars 2021, 09:00-18:00


Description


Type d'UE
Méthodologie
Disciplines
Économie, Méthodes et techniques des sciences sociales, Sociologie
Page web
-
Langues
anglais
Mots-clés
-
Aires culturelles
-

In the social sciences, multiple correspondence analysis (MCA) is a statistical technique that perhaps has become best known through the work of the late Pierre Bourdieu (1930-2002), in particular “Distinction” (Bourdieu 1984), “Homo Academicus” (Bourdieu 1988) and “The State Nobility” (Bourdieu 1996). In more recent years, the technique has found a wider audience, and is now used by social scientists in several disciplines.

As a counterpart to principal component analysis (PCA), a geometric technique for the analysis of metric variables, MCA is a geometric technique for the analysis of categorical or categorized variables. Originating in the early 1960s and the French statistician Jean-Paul Benzécri’s work in mathematical linguistics, MCA represents and models data sets as clouds of points in a multidimensional Euclidean space. The interpretation of the data is based on these clouds of points. By combining MCA with inferential techniques and variance analysis, we arrive at an integrated framework of interpretation that also is known under the name of Geometric Data Analysis (GDA).

In a combination of lectures and laboratory exercises, this course will introduce students to the fundamental properties, procedures and rules of interpretation of the most commonly used forms of correspondence analysis, i.e. simple correspondence analysis (CA) and MCA, and also to the most commonly used software. A main emphasis will be put on how to use MCA in one’s own work, and on practical examples and applications. Particular attention will therefore be paid to how MCA can be used in the construction of social spaces.

Le programme détaillé n'est pas disponible.


Master


  • Institutions, organisations, économie et société – M1/S2-M2/S4
    Suivi et validation – semestriel quotidienne = 3 ECTS
    MCC – contrôle continu

Renseignements


Contacts additionnels
-
Informations pratiques
-
Direction de travaux des étudiants
-
Réception des candidats
-
Pré-requis
-