Dokuz Eylül University Information Package / Courses Catalog

Description of Individual Course Units

Course Unit Code	Course Unit Title	Type Of Course	D	U	L	ECTS
STA 5058	MULTIVARIATE STATISTICS	ELECTIVE	3	0	0	8

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR ESIN FIRUZAN

Offered to

Statistics
Statistics
STATISTICS

Course Objective

The objective of this course is to cover a high level of Multivariate Statistics and its applications.

Learning Outcomes of the Course Unit

1	Understanding statistical concepts of linear algebra terms (rank, determinant, eigenvalu, eigenvector etc.),
2	Obtaining multivariate descriptive statistics (mean vector, variance-covariance matrix, correlation matrix etc.),
3	Interpreting three or more dimensional graphs,
4	Applying Principal Component Analysis,
5	Applying Factor Analysis,
6	Applying Discriminant Analysis for two multivariate normal populations.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week	Subject	Description
1	Types of variables, Data Matrices and Vectors, Data Subscripts
2	The Multivariate Normal Probability Density Function, Bivariate Normal Distributions
3	Mean Vectors and Variance-Covariance, Correlation and Standardized data matrices
4	Three-Dimensional Data Plots, Plots of Higher Dimensional Data, Preparing Individual Assignments
5	Multivariate Normal Distribution Contour Plot
6	Eigenvalues and eigenvectors, Geometric Descriptions
7	Eigenvalues and eigenvectors, Geometric Descriptions
8	Principal Components Analysis on the Variance-Covariance Matrix , Preparing Individual Assignments
9	Estimation of Principal Components, PCA on the Correlation Matrix P
10	Objectives of Factor Analysis, Factor Analysis Equations, Preparing Individual Assignments
11	Choosing the Appropriate Number of Factors, Rotating Factors
12	Classification and Discriminant for two Multivariate Normal Populations, Preparing Individual Assignments
13	Cost Functions and Prior Probabilities,
14	A General Discriminant Rule (Two Populations)

Recomended or Required Reading

Textbook(s): Johnson, R.A. ve Wichern, D.W., (2007), Applied Multivariate Statistical Analysis, 6th Edn, Pearson International Edition.
Supplementary Book(s): Johnson, D.E. (1998) Applied Multivariate Methods for Data Analysts, Duxbury.

Planned Learning Activities and Teaching Methods

Lecture, homework assignments, problem solving, presentation

Assessment Methods

SORTING NUMBER	SHORT CODE	LONG CODE	FORMULA
1	ASG	ASSIGNMENT
2	FIN	FINAL EXAM
3	FCG	FINAL COURSE GRADE	ASG * 0.50 + FIN * 0.50
4	RST	RESIT
5	FCGR	FINAL COURSE GRADE (RESIT)	ASG * 0.50 + RST * 0.50

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

Further Notes About Assessment Methods

If the instructor needs to add some explanation or further note, this column can be selected from the DEBIS menu.

Assessment Criteria

Evaluation of homework assignments, presentation, project report and final exam

Language of Instruction

English

Course Policies and Rules

Attendance to at least 70% for the lectures is an essential requirement of this course and is the responsibility of the student. It is necessary that attendance to the lecture and homework delivery must be on time. Any unethical behavior that occurs either in presentations or in exams will be dealt with as outlined in school policy. You can find the undergraduate policy at http://web.deu.edu.tr/fen

Contact Details for the Lecturer(s)

DEU Fen Fakültesi Istatistik Bölümü
e-posta: s.alpaykut@deu.edu.tr
Tel: 0232 301 85 56

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities	Number	Time (hours)	Total Work Load (hours)
Lectures	14	3	42
Preparations before/after weekly lectures	14	2	28
Preparation for final exam	1	36	36
Preparing assignments	4	25	100
Final	1	2	2
TOTAL WORKLOAD (hours)			208

Contribution of Learning Outcomes to Programme Outcomes

PO/LO	PO.1	PO.2	PO.3	PO.4	PO.6	PO.8	PO.9	PO.10
LO.1	5	5	5		5	5	5	5
LO.2	5	5	5		5		5	5
LO.3	5	5		5	5		5	5
LO.4	5		5	5	5		5	5
LO.5	5				5		5	5
LO.6	5				5	5	5	5

COURSE UNIT TITLE

DEGREE PROGRAMMES

Description of Individual Course Units

Offered By

Level of Course Unit

Course Coordinator

Offered to

Course Objective

Learning Outcomes of the Course Unit

Mode of Delivery

Prerequisites and Co-requisites

Recomended Optional Programme Components

Course Contents

Recomended or Required Reading

Planned Learning Activities and Teaching Methods

Assessment Methods

Further Notes About Assessment Methods

Assessment Criteria

Language of Instruction

Course Policies and Rules

Contact Details for the Lecturer(s)

Office Hours

Work Placement(s)

Workload Calculation

Contribution of Learning Outcomes to Programme Outcomes

CONTACT INFORMATION