Workshop on Simple and Multiple Correspondence Analysis


The department of Social Sciences and Institute for Migration Studies organized a three-day workshop  from October 9-11 on Simple and Multiple Correspondence Analysis.  

Combining both lectures and laboratory exercises, this 20-hour course introduced faculty and 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), multiple correspondence analysis (MCA) and cluster analysis.

In the social sciences, MCA is a statistical technique that first and foremost has become 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).

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.

Dr. Jennifer Skulte-Ouaiss, a political scientist and faculty member in the department, found the workshop “very well organized and clear. Dr. Hjellbrekke is clearly a leader in the field as well as an excellent teacher of research methods. An excellent workshop. I’m already thinking how I can use MCA on my current research on threat construction and terrorism policies in the United States”. 

Rami Abi Rafeh, an M.A. student, considered the three-day workshop a “huge success” and a fellow student, Aaron Miller, also thought it was very informative, stating: “I gained a new research technique and expanded my understanding of statistics and statistical methods.”

Mariam Hasbani, a Ph.D. student, will seriously consider applying this new technique in her ongoing research on ‘Academic international mobility and knowledge production: the case of Lebanon’.

Update: the lectures given during the workshop can now be accessed here. (Access provided to Social Sciences students).