Master 2025/2026

Multidimensional Data Analysis

Type: Elective course (Data Analytics and Social Statistics)

Delivered by: International Laboratory for Applied Network Research

When: 1 year, 4 module

Open to: students of one campus

Instructors: Irina Pavlova

Language: English

Course Syllabus

Abstract

This course takes a modern, data-analytic approach to the multivariate data. Multivariate data analysis (MVA) encompasses statistical techniques that are used to analyze several variables at once. The course covers some basic notions of statistics with the development into several domains: cluster analysis, principle component analysis, factor analysis, canonical corelation analysis, discriminant analysis. All the topic of the course are supplemented by the examples of MVA application to different types of data. This course serves as an important prerequisite for the course in structural equation modeling.