Exploratory multivariate data analysis is studied and teached in a French-way since a long time in France. This course focuses on four essential and basic methods, those with the largest potential in terms of applications: principal component analysis (PCA) when variables are quantitative, correspondence analysis (CA) and multiple correspondence analysis (MCA) when variables are categorical and clustering.
This course is application-oriented; formalism and mathematics writing have been reduced as much as possible while examples and intuition have been emphasized and the numerous exercises done with FactoMineR (a package of the free R software) will make the participant efficient and reliable face to data analysis.
We hope that with this course, the participant will be fully equipped (theory, examples, software) to confront multivariate real-life data.
An undergraduate level is quite sufficient to capture all the concepts introduced.
Basic knowledges in statistics are necessary, such as: correlation coefficient, chi-squared test, one-way ANOVA.
On the sofware side, an introduction to the R language is sufficient, at least at first.