2025/2026

Непараметрическая теория и методы анализа данных

Статус: Маго-лего

Когда читается: 3, 4 модуль

Охват аудитории: для своего кампуса

Преподаватели: Пашков Станислав Георгиевич

Язык: английский

Кредиты: 6

Контактные часы: 40

Course Syllabus

Abstract

This course is devoted to a separate section of statistical theory dealing with non-parametric methods of statistical data analysis (non-parametric statistics, NPS). This section of statistics is very often used in conjunction with more “classical” approaches based on Gaussian statistics, but it is arranged differently and requires a special approach to understanding and interpretation. Currently, more and more business decisions are made on the basis of data measured in categorical and rank scales, and therefore the relevance of this type of data analysis is increasing. Throughout the course, students will receive a theoretical and practical understanding of how to approach the procedure of non-parametric data analysis, on what types of data it is possible to do this, what needs to be considered and how to interpret the data. A special place in the course is occupied by rank regression and loglinear regression as special cases of working with data that do not have a Gaussian distribution. All the learning process is based on R language with special libraries.