Multivariate data analysis Level 2

main objectives

Be able to ‘identify’ data, organize it and then build a predictive model from a data analysis method ,Know the advantages, disadvantages, and limitations of a model,Be able to understand and apply the mathematical underpinnings of the methods used,Know how to use R software analysis scripts (https://www.r-project.org/),Be able to describe and interpret the results obtained using R software,To be able to present your results in public in the form of a slideshow,,

general content

Simple linear regression,Multiple linear regression,Discriminant Analysis (geometric and Bayesian methods), scoring concept,Introduction to Machine Learning: Segmentation Methods (CART),

pedagogy

6 CM sessions of 1.5 hours ,5 TD sessions of 1.5 hours ,,A laptop with a web browser and wifi access to esa’s network is essential in TD,

evaluation

Written exam : Interpreting the results of a dataset analysis ,,