Subject

Multivariate Statistical Analysis

Course Title

Multivariate Statistical Analysis
Multivariate statistical analysis

Code

m23_s_053

Study Programme

—

Organizer of the study programme (unit, institute, department or division)

Faculty of Computer Science and Engineering

Degree level (first, second, third cycle)

Second cycle

Academic year / semester

10 / Summer

Number of ECTS credits

Teacher

Alexandra Dedinec, Ilinka Ivanoska, Marija Mihova

Prerequisites for enrolling in the course

—

10.

Objectives of the course programme (competences)

Students to learn to
use the methods of multidimensional statistical analysis with
Generalization of the widely used one-dimensional methods. To
Understand the covariant structure in the analysis of multidimensional data.
data. To learn to choose and apply appropriate methods for
extraction, systematization, and analysis of the information contained in
multidimensional data.

11.

Course content

Multidimensional normal
Distribution and drawing conclusions about the vector of the mathematical
Expectation. Cluster analysis and discriminant analysis. Principal component analysis.
components and factor analysis. Canonical correlation analysis.

12.

Learning methods

lectures, laboratory exercises, project work, and independent study.

13.

Total available time

6 ECTS x 30 hours = 180 hours

14.

Distribution of available time

60 + 30 + 60 + 0 + 30 = 180 hours

15.

Forms of teaching activities

15.1.	Lectures - theoretical instruction	60 hours
15.2.	Exercises (laboratory, auditory), seminars, teamwork	30 hours

16.

Other forms of activities

16.1.	Project assignments	0 hours
16.2.	Independent assignments	60 hours
16.3.	Home study	30 hours

17.

Assessment method

17.1.	Tests	0 points
17.2.	Seminar paper / project (presentation: written and oral)	0 points
17.3.	Activities and learning	0 points
17.4.	Final exam	0 points

18.

Grading criteria (points / grade)

up to 50 points	5 (five) (F)
from 51 to 60 points	6 (six) (E)
from 61 to 70 points	7 (seven) (D)
from 71 to 80 points	8 (eight) (C)
from 81 to 90 points	9 (nine) (B)
from 91 to 100 points	10 (ten) (A)

19.

Requirement for obtaining a signature and taking the final exam

A minimum of 101 TP3T from the points of each of the quizzes, completed project assignments.

20.

Language of instruction

Macedonian or English

21.

Method for monitoring the quality of teaching

Analysis of the results achieved, anonymous student survey on the quality of instruction

22.

Literature

22.1.	Required literature 1. Theodore W. Anderson \| An Introduction to Multivariate Statistical Analysis \| Wiley \| 2003 2. Klaus Backhaus, Bernd Erichson, Sonja Gensler, Rolf Weiber, Thomas Weiber \| Multivariate Analysis: An Application-Oriented Introduction \| Springer Gabler \| 2021 3. Everitt, B. and Dunn, G. \| Applied Multivariate Data Analysis \| Arnold \| 2001
22.2.	Additional literature No. Author Title Publisher Year