Delivered at:: Big Data and Information Retrieval School

Course type:: Elective course

When:: 3 year, 3, 4 module

Instructor

Slabolitskiy, Ilya S.

Full Syllabus Ask Question

Abstract

Classical (mathematical) statistics usually turns out to be unsustainable and unrobust to real problems. Many data analysis tasks (in economics, finance and business) require alternative, more complex and advanced approaches, which will be applicable in practice. In this course, we will discuss a great amount of such topics. We will talk about their theoretical (mathematical and probabilistic) foundations and see how they can be applied to the practical problems.

Learning Objectives

this course is focused on modern, complex and advanced data analysis methods, provides their overview, mathematical foundations and demonstrates their applications

Expected Learning Outcomes

orms the ideas of semi-parametric and non-parametric statistics
forms the ideas of copulae-based models.
forms the ideas of online statistical learning.
forms the ideas of elements of extreme value analysis.

Course Contents

semi-parametric and non-parametric statistics
copulae-based models
online statistical learning
elements of extreme value analysis

Assessment Elements

home assignments
home assignments during the course
midterm 1
midterm based on the 3 module
midterm 2
midterm based on the 4 module
exam
final exam

Interim Assessment

2025/2026 4th module
0.3 * exam + 0.2 * home assignments + 0.25 * midterm 1 + 0.25 * midterm 2

Bibliography

Recommended Core Bibliography

All of nonparametric statistics : with 52 ill., Wasserman, L., 2006
Wasserman, L. All of nonparametric statistics. – Springer Science & Business Media, 2006. – 270 pp.

Recommended Additional Bibliography

All of statistics : a concise course in statistical inference, Wasserman, L., 2010

Authors

SLABOLITSKII ILIA SERGEEVICH
Абдулхакимов Мухиддин Мураджанович

Bachelor’s Programme 'Data Science and Business Analytics'

Advanced Statistical Methods