MATH-444 / 5 credits

Teacher: Panaretos Victor

Language: English


Summary

Multivariate statistics focusses on inferring the joint distributional properties of several random variables, seen as random vectors, with a main focus on uncovering their underlying dependence structure. This course offers a broad introduction to its concepts, methods & theory

Content

Learning Prerequisites

Required courses

A solid introduction to probability (e.g. MATH-230) and statistics (e.g. MATH-240). Basic knowlege of linear models (e.g. MATH-341) is useful but not necessary.

Learning Outcomes

By the end of the course, the student must be able to:

  • Manipulate the multivariate normal distribution and some of its extensions.
  • Expound the main concepts in coupling and copulas
  • Expound and apply the main dependence measures.
  • Apply a canonical correlation analysis to some concrete cases.
  • Apply a principal component analysis to some concrete cases.
  • Perform basic multivariate hypothesis tests.
  • Demonstrate a basic understanding of linear discriminant analysis.
  • Demonstrate a basic understanding of graphical models theory.
  • Demonstrate his/her understanding of the main mathematical concepts/proofs of the course.
  • Justify the use of a method for a particular data set and objective

Teaching methods

Lecture ex cathedra using slides as well as the blackboard.

 

Assessment methods

Written examination.

Dans le cas de l'art. 3 al. 5 du Règlement de section, l'enseignant décide de la forme de l'examen qu'il communique aux étudiants concernés.

Supervision

Office hours No
Assistants Yes
Forum Yes

Resources

Virtual desktop infrastructure (VDI)

No

Bibliography

  • Theodore W. Anderson: Multivariate Analysis, Wiley

Ressources en bibliothèque

Notes/Handbook

The slides will be available on Moodle.

Moodle Link

In the programs

  • Semester: Spring
  • Exam form: Written (summer session)
  • Subject examined: Multivariate statistics
  • Lecture: 2 Hour(s) per week x 14 weeks
  • Exercises: 2 Hour(s) per week x 14 weeks
  • Semester: Spring
  • Exam form: Written (summer session)
  • Subject examined: Multivariate statistics
  • Lecture: 2 Hour(s) per week x 14 weeks
  • Exercises: 2 Hour(s) per week x 14 weeks
  • Semester: Spring
  • Exam form: Written (summer session)
  • Subject examined: Multivariate statistics
  • Lecture: 2 Hour(s) per week x 14 weeks
  • Exercises: 2 Hour(s) per week x 14 weeks
  • Semester: Spring
  • Exam form: Written (summer session)
  • Subject examined: Multivariate statistics
  • Lecture: 2 Hour(s) per week x 14 weeks
  • Exercises: 2 Hour(s) per week x 14 weeks
  • Semester: Spring
  • Exam form: Written (summer session)
  • Subject examined: Multivariate statistics
  • Lecture: 2 Hour(s) per week x 14 weeks
  • Exercises: 2 Hour(s) per week x 14 weeks

Reference week

 MoTuWeThFr
8-9     
9-10     
10-11     
11-12     
12-13     
13-14   MAA110 
14-15    
15-16   MAA110 
16-17    
17-18     
18-19     
19-20     
20-21     
21-22     

Thursday, 13h - 15h: Lecture MAA110

Thursday, 15h - 17h: Exercise, TP MAA110

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