Aim of the course is to provide the student with an adequate preparation on the statistical concepts and methods that can be used to collect, elaborate and synthesize data concerning economical and social phenomena.
Much attention will be paid to conditions that need to be fulfilled for the different tecniques to be appliable, stressing their analytical potentialities. The course is focused mainly on applications of the different tecniques.
Much attention will be paid to conditions that need to be fulfilled for the different tecniques to be appliable, stressing their analytical potentialities. The course is focused mainly on applications of the different tecniques.
teacher profile teaching materials
Data reduction: composite indicators, principal component analysis
Cluster analysis
An Introduction to Applied Multivariate Analysis with R, B. Everitt, T. Hothorn, Springer.
Programme
Relationship between two or more variables: independence, association; concordance. Linear regression; Multiple regression. Case studies.Data reduction: composite indicators, principal component analysis
Cluster analysis
Core Documentation
Introductory Statistics with R, P. Dalgaard, Springer.An Introduction to Applied Multivariate Analysis with R, B. Everitt, T. Hothorn, Springer.
Reference Bibliography
Introductory Statistics with R, P. Dalgaard, Springer. An Introduction to Applied Multivariate Analysis with R, B. Everitt, T. Hothorn, Springer.Type of delivery of the course
lectures in a class room and excercises in computer lab.Type of evaluation
For those who follow the lectures the examination can consist either in a written case study that will be illustrated in front of the class or in the elaboration of a data set (supplied by the examiners) and in the oral discussion of the outcome.