COURSE UNIT TITLE

: MULTIVARIATE STATISTICAL MODELS

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
EKO 6036 MULTIVARIATE STATISTICAL MODELS ELECTIVE 3 0 0 6

Offered By

Economics

Level of Course Unit

Third Cycle Programmes (Doctorate Degree)

Course Coordinator

ASSOCIATE PROFESSOR KADIR ERTAŞ

Offered to

Economics

Course Objective

To internalize models that explain economic theory with the help of advanced econometric analysis techniques and discuss findings of applied literature.

Learning Outcomes of the Course Unit

1   To be able to form factor model and implement it in random samples by p-variable.
2   To be able to understand discriminant model and implement it in random samples by p-variable.
3   To be able to understand assumptions of canonical correlation analysis, it s theory and disjunction structure of p×1 random vector.
4   To be able to understand and implement clustering analysis

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Maximum Likelihood Theory for Normal Distribution Model with p-variable
2 Maximum Likelihood Theory for Normal Distribution Model with p-variable
3 Factor Analysis and Its implementation
4 Factor Analysis and Its implementation
5 Factor Analysis and Its implementation
6 Discriminant Analysis and Its implementation
7 Discriminant Analysis and Its implementation
8 Midterm
9 Canonical Correlation Analysis and It s implementation
10 Canonical Correlation Analysis and It s implementation
11 Canonical Correlation Analysis and It s implementation
12 Clustering Analysis and It s implementation
13 Clustering Analysis and It s implementation

Recomended or Required Reading

Multivariate Analysis, Academic Press , K.V. Mardia, J.T. Kent, J.M. Biby.

Planned Learning Activities and Teaching Methods

This course will be presented using methods of expression, discussion and solving problem.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 STT TERM WORK (SEMESTER)
3 FIN FINAL EXAM
4 FCG FINAL COURSE GRADE MTE * 0.25 + STT * 0.25 + FIN* 0.50
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE* 0.25 + STT * 0.25 + RST* 0.50


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

To be announced.

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lecture 13 3 39
Weekly course preparation 13 4 52
Personal homework study 1 25 25
Other short exam study 1 20 20
Preparing presentation 1 20 20
Midterm 1 3 3
Final 1 3 3
TOTAL WORKLOAD (hours) 162

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9
LO.1144
LO.21144
LO.31245
LO.42455