Information Package / Course Catalogue
Multivariate Statistical Methods-Iı
Course Code: BİS620
Course Type: Area Elective
Couse Group: Third Cycle (Doctorate Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 2
Prt.: 2
Credit: 3
Lab: 0
ECTS: 4
Objectives of the Course

To provide the gaining the ability of performing advanced multivariate analysis.

Course Content

Multivatiate normal distribution, inferences in multivariate means and linear models. Principle components, factor analysis, discriminant analysis, cluster analysis, correspondence analysis.

Name of Lecturer(s)
Learning Outcomes
1.Discuss when to use common multivariate statistical methods
2.Discuss the strength and weaknesses of the multivariate statistical methods.
3.Interpret results from articles that have applied multivariate statistics
4.Describe the design of a study with respect to the multivariate statistical methods.
5.Gaining the ability to use multivariate statistical methods
Recommended or Required Reading
Weekly Detailed Course Contents
Week 1 - Theoretical
Boxplot/Histogram/Scatter-plot - I
Week 1 - Practice
Application with package programs
Week 2 - Theoretical
Boxplot/Histogram/Scatter-plot - II
Week 2 - Practice
Application with package programs
Week 3 - Theoretical
Matrix Theory in Multivarite Statistical Analysis - I
Week 3 - Practice
Application with package programs
Week 4 - Theoretical
Matrix Theory in Multivarite Statistical Analysis - II
Week 4 - Practice
Application with package programs
Week 5 - Theoretical
Multivariate Normal Distributions
Week 5 - Practice
Application with package programs
Week 6 - Theoretical
Multivariate analysis of variance- MANOVA - I
Week 6 - Practice
Application with package programs
Week 7 - Theoretical
Multivariate analysis of variance-MANOVA - II
Week 7 - Practice
Application with package programs
Week 8 - Theoretical
Literature review and discussion (Midterm exam)
Week 9 - Theoretical
Multivariate Regressions - I
Week 9 - Practice
Application with package programs
Week 10 - Theoretical
Multivariate Regressions - II
Week 10 - Practice
Application with package programs
Week 11 - Theoretical
Principal Component Analysis
Week 11 - Practice
Application with package programs
Week 12 - Theoretical
Factor Analysis
Week 12 - Practice
Application with package programs
Week 13 - Theoretical
Cluster Analysis
Week 13 - Practice
Application with package programs
Week 14 - Theoretical
Discriminant 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
Quiz2216
Midterm Examination110212
Final Examination115217
TOTAL WORKLOAD (hours)96
Contribution of Learning Outcomes to Programme Outcomes
PÇ-1
PÇ-2
PÇ-3
PÇ-4
PÇ-5
PÇ-6
PÇ-7
OÇ-1
4
3
3
4
4
3
4
OÇ-2
4
4
4
5
4
4
3
OÇ-3
4
4
4
4
3
5
4
OÇ-4
2
4
3
4
4
5
3
OÇ-5
Adnan Menderes University - Information Package / Course Catalogue
2026