Information Package / Course Catalogue
Applied Multivariate Statistical Methods-Iı
Course Code: BİS520
Course Type: Area Elective
Couse Group: Second Cycle (Master's Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 2
Prt.: 2
Credit: 3
Lab: 0
ECTS: 4
Objectives of the Course

Classification and examining the dependency structure with dimensionality decomposition in multivariate data sets and hypothesis tests

Course Content

Principal component analysis, factor analysis, canonical correlation analysis, discriminant analysis, cluster analysis, multi-dimensional scaling, correspondence analysis

Name of Lecturer(s)
Learning Outcomes
1.To be able to analyse multivariate statistics with several data sets by using statistical softwares such as SPSS, Statistica, Systat, Minitab
2.To be able to apply the multivariate statistical methods with theoretical or real life data sets by using related statistical softwares. Homework preparation and presentations.
3.To learn how to apply Principal component analysis, factor analysis
4.To learn how to do multi-dimensional scaling and correspondence analysis
5.To be able to analyse Canonical correlations, Discriminant analysis and Cluster analysis
Recommended or Required Reading
Weekly Detailed Course Contents
Week 1 - Theoretical
Principal component analysis, obtaining principal components, determining the number of principal components and application
Week 1 - Practice
Application with package programs
Week 2 - Theoretical
Introduction to factor analysis, the differences between factor analysis and principal component analysis and factor models
Week 2 - Practice
Application with package programs
Week 3 - Theoretical
Principal coefficients and scores, factor rotation methods
Week 3 - Practice
Application with package programs
Week 4 - Theoretical
The aim of canonical correlation analysis, definitions of canonical variables and obtaining these variables
Week 4 - Practice
Application with package programs
Week 5 - Theoretical
Obtaining canonical correlations, the significance tests of canonical correlations.
Week 5 - Practice
Application with package programs
Week 6 - Theoretical
Introduction to discriminant analysis, basic assumptions of discriminant analysis
Week 6 - Practice
Application with package programs
Week 7 - Theoretical
Determining discriminant functions
Week 7 - Practice
Application with package programs
Week 8 - Theoretical
Literature review and discussion (Midterm exam)
Week 9 - Theoretical
The significance test of canonical function, Two and multi-group classification in discriminant analysis
Week 9 - Practice
Application with package programs
Week 10 - Theoretical
The significance test of canonical function, Two and multi-group classification in discriminant analysis
Week 10 - Practice
Application with package programs
Week 11 - Theoretical
Introduction to clustering analysis, similarity and distance metrics using for clustering
Week 11 - Practice
Application with package programs
Week 12 - Theoretical
Clustering methods and determining the number of clusters
Week 12 - Practice
Application with package programs
Week 13 - Theoretical
Introduction to multi-dimensional analysis and multi-dimensional methods
Week 13 - Practice
Application with package programs
Week 14 - Theoretical
Correspondence analysis
Week 14 - Practice
Application with package programs
Week 15 - Final Exam
Final exam
Assessment Methods and Criteria
Type of AssessmentCountPercent
Attending Lectures1%5
Assignment1%5
Midterm Examination1%20
Final Examination1%70
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory140228
Lecture - Practice140228
Assignment1505
Quiz42112
Midterm Examination110212
Final Examination115217
TOTAL WORKLOAD (hours)102
Contribution of Learning Outcomes to Programme Outcomes
PÇ-1
PÇ-2
PÇ-3
PÇ-4
PÇ-5
PÇ-6
PÇ-7
PÇ-8
PÇ-9
PÇ-10
OÇ-1
4
4
4
4
5
5
5
5
5
5
OÇ-2
5
4
4
4
4
4
3
4
5
5
OÇ-3
4
5
4
4
4
5
4
3
5
5
OÇ-4
OÇ-5
5
5
4
4
4
4
3
5
5
4
Adnan Menderes University - Information Package / Course Catalogue
2026