Advanced Multivariate Statistics
A.Y. 2024/2025
Learning objectives
This course is divided in two parts: (i) inference for multivariate analysis and (ii) exploratory multivariate analysis. The first part takes up the concepts of inferential multivariate statistical analysis, extending the theory about univariate inferential statistics with all the implications this extension involves. Additional topics in this context are Bayesian networks and multivariate bootstrapping. The second part will focus on exploratory multivariate analysis and will focus on further dimensional reduction techniques, correlation analysis and advanced clustering. During the course, applications to real situations will be presented using mainly the R statistical package.
Expected learning outcomes
Students will achieve skills for doing independent study and research in presence of multivariate data. Moreover, they will learn how to use dedicated R libraries to deal with multivariate contexts.
Lesson period: First trimester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Responsible
Lesson period
First trimester
Professor(s)
Reception:
Wednesday, 3PM-5PM. Starting from January 8, 2024 office hours will be ONLY by appointment and remotely via the Teams platform. Office hours on Wednesday March 6th are postponed to Thursday March 7th at 3PM
Room 37, 3rd Floor, Department of Economics, Management and Quantitative Methods.