1. Principal Component Analysis

2. Multiple Correspondence Analysis

3. Factorial Analysis of Mixed Data

4. Weighting Groups of Variables

5. Comparing Clouds of Partial Individuals

6. Factors Common to Different Groups of Variables

7. Comparing Groups of Variables and Indscal Model

8. Qualitative and Mixed Data

9. Multiple Factor Analysis and Procrustes Analysis

10. Hierarchical Multiple Factor Analysis

11. Matrix Calculus and Euclidean Vector Space