Analyse des données - Approche multicritèresSciences pour l'ingénieur 1 (ERE)

Mastering techniques for the analysis of large data sets (many variables and many individuals), qualitative and quantitative: linear model, multiple regression, variance analysis, factorial methods: principal component analysis (ACP), factorial correspondence analysis (FAC), multiple correspondence analysis (MCA), discriminant analysis, hierarchical and non-hierarchical classification methods. Know the application of multidimensional data analysis methods to data mining.

Chapter 1: Exploratory methods: factorial analyses. • Analysis in main components. • Factorial analysis of correspondence. • Discriminatory analysis.

Chapter 2: Classification. • Mobile centre method. • Hierarchical classification

Chapter 3: Modelling methods: the linear model. • Linear regression. • Nonlinear regression. • Analysis of variance.

Chapter 4: Towards "Data mining". • Use of Excel software

Table Control (Duration 1h30)