This 5th edition of the MOOC starts on March 2, 2020.
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. An extension to Multiple Factor Analysis (MFA) will give you the opportunity to analyse more complex dataset that are structured by groups.
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.
Week 1. Principal Component Analysis
Data - Practicalities
Studying individuals and variables
Aids for interpretation
PCA in practice using FactoMineR
Week 2. Correspondence Analysis
Data - introduction and independence model
Visualizing the row and column clouds
Inertia and percentage of inertia
Correspondance Analysis in practice using FactoMineR
Week 3. Multiple Correspondence Analysis
Data - issues
Visualizing the point cloud of individuals
Visualizing the point cloud of categories - simultaneous representation
Multiple Correspondance Analysis in practice using FactoMineR
Week 4. Clustering
An example, and choosing the number of classes
Partitioning methods and other details
Characterizing the classes
Clustering in practice using FactoMineR
Week 5 : Multiple Factor Analysis
Data - issues
Balancing groups and choosing a weighting for the variables
Studying and visualizing the groups of variables
Visualizing the partial points
Visualizing the separate analyses
Taking into account groups of categorical variables
Taking into account contingency tables
Multiple Factor Analysis in practice using FactoMineR
Jérôme Pagès, François Husson and Magalie Houée-Bigot
Axel Schwanke completed this course, spending 10 hours a week on it and found the course difficulty to be medium.
This is an excellent course covering all of the chapters of François Husson's book "Exploratory Multivariate Analysis by Example Using R". There are a lot of practical examples and quizzes after each video and exercises at the end of each week. At the of the course one gets not only a good understanding of the different methods and their application areas, but also knows which of the many functions of the FactoMineR R package to use and how to build a data analysis results report.