Dokuz Eylül University Information Package / Courses Catalog

General Description

History

Established within the Faculty of Arts and Sciences, the Department of Statistics started postgraduate education in the 1994-1995 academic year. Under the Department of Statistics, Master Degree in Statistics Master Degree in Statistics Scientific Preparation, Master Degree in Data Science (with and without Thesis), Doctorate Degree in Statistics programs are carried out. The graduate program of the Department of Statistics is 100% in English. The program aims to train students who can independently collect data and produce information using both theoretical and applied statistical concepts at the graduate level. Educational opportunities are offered to have a statistical perspective and to contribute to the solution of problems arising in other disciplines. The aim of the program is to equip people who aim to pursue a career in fields such as Statistics, Data Science, Data Analytics, Machine Learning, Artificial Intelligence, Big Data, and experts who want to do academic work, with advanced Statistics theory and programming knowledge and skills. The compulsory and elective courses of the program cover the theory and applications of Statistics, as well as an intensive computer programming content. Basically, it is aimed that students gain the skills of accessing information, and improve their ability to evaluate and interpret the information they have obtained.

Qualification Awarded

Ph.D. in Statistics

Level of Qualification

Third Cycle (Doctorate Degree)

Specific Admission Requirements

Second Cycle Degree in the same or in related disciplines. Acceptable score on ALES (Academic Personnel and Graduate Education Entrance Exam) (at least 60) or Equivalent GRE, GMAT score. Acceptable score on Language Proficiency Tests. Acceptable weighted score based on the first or second cycle (with thesis) cumulative grade point average (GPA) and ALES score. However, ALES requirement is waived for the graduates of doctorate /arts proficiency/medical residency/ dental residency/ veterinary residency/ pharmaceutical residency programs as well as for the admissions to the graduate programs offered by the Conservatory and the departments of Fine Arts Faculty, where students are admitted only by the Artistic Aptitude Test. Final admission is based on the evaluation of the related academic unit committee. International student admission requirements are decided by the Graduate School Executive Committee.

Foreign language proficiency requirement is a score of at least 55 points (taken within the last 5 years) in YDS, e-YDS and YÖKDİL (English) from the central foreign language exam conducted by ÖSYM, or an equivalent score from any of the exams whose equivalence is accepted by the ÖSYM Executive Board ( https://denklik.yok.gov.tr/yabanci-dil-esdegerliği).

Specific Arrangements for Recognition of Prior Learning (Formal, Non-Formal and Informal)

According to the Regulations of Dokuz Eylül University for Graduate Schools, students may be accepted for graduate transfer with the approval of the Department Directorate and decision of the Board of Directors of the Graduate School in case the student fulfills the graduate transfer regulations decided by the General Council of the Graduate School. Previously taken courses at another graduate programme with a successful grade may be recognized by the related programmes with the written request of the students including course contents and the transcript, and by the recommendation of the Department Directorates and by the decision of the Board of Directors. The courses taken by the outgoing Exchange students may have the recognition at the school either as compulsory or elective by the decision of the Board of Directors.

Qualification Requirements and Regulations

4 years, 2 semesters per year, 16 weeks per semester, 240 ECTS in total.

Profile of the Programme

The aim of the doctorate program in Statistics is to equip students with theoretical and practical statistical information and values that should be possessed by decision makers with analytical and critical thinking skills. In addition, the program provides the necessary equipment for those who aim to pursue a career in fields such as Statistics, Data Science, Data Analytics, Machine Learning, Artificial Intelligence, Big Data, by combining the knowledge and skills of Statistics theory and computer programming. It aims to graduate students who can follow the innovations in science and technology and constantly renew their knowledge of statistics with the awareness of lifelong learning.

The language of instruction of the doctorate program in Statistics is 100% in English. In addition, our department has bilateral agreements with various universities within the scope of ERASMUS and FARABI programs. There are 21 lecturers in our department.

Key Learning Outcomes

1	To have an advanced level theory and application backround in statistics.
2	To have an advanced level literature knowledge about his/her dissertation .
3	To publish at least one research paper about his/her dissertation in a SCI or SCI-EXP journal.
4	To propose a new method or an approach for a problem related with his/her dissertation.
5	To be able to superwise a research which is about his/her dissertation.
6	To understand and interpret new statistical methods and approaches in a systematic manner.
7	To understand the interaction with statistics and other disciplines and to use his/her statistical backround while evaluating new ideas.
8	To defend ideas about his/her statistical research area in a professional community.
9	To have advanced communication skills in at least one foreing language as verbal, visual or written.
10	By improving the sense of statistics science in a community, to contribute the process of being an information society.

Occupational Profiles of Graduates with Examples

Our graduates can be employed in Universities as academicians, Research and Planning departments of Public and Private Organizations, at Finance and Insurance Companies as an expert or manager, also in software-informatics departments, they can get career opportunities at many levels as statistics specialist, system analyst, data scientist, process analyst, database manager, operations manager, market researcher, business analyst, software developer, etc.

Access to Further Studies

May apply to post doctorate programmes.

Course Structure Diagram with Credits

Semester	No	Course Unit Code	Course Unit Title	Course Unit Type	T	P	L	ECTS
In addition to the compulsory courses of the programme, students register to elective courses appropriate for their thesis topic, on the consent of their supervisor. If necessary, on the consent of their supervisor, they can also register to courses from other programmes (from DEU or other universities). It is obligatory to register the compulsory courses with approval of the supervisor. In the case of one of these courses taken during the M.Sc. education, these are not obligatory. The registration must be noticed to the Institute during course registration period by the supervisor. For Ph. D. students it is obligatory to take minimum 2 non-credit courses among "Ph. D. Programs Common Elective Courses" and be successful with grade (B) within 4 semesters of course taking period.
T: Theoretical P: Practice L: Laboratory B: Spring Semester G: Fall Semester H: Full Year

1 .Semester:
G	1	MAT 5102	NUMERICAL AND APPROXIMATE METHODS	COMPULSORY	3	0	0	9
G	2	STA 5053	PROBABILITY AND STATISTICAL INFERENCE - I	COMPULSORY	3	0	0	8
G	0	-	ELECTIVE COURSE	ELECTIVE	-	-	-	13
TOTAL:								30

2 .Semester:
Semester	No	Course Unit Code	Course Unit Title	Course Unit Type	T	P	L	ECTS
B	1	FBE 6668	PHILOSOPHY OF SCIENCE AND ETHICS	COMPULSORY	3	0	0	5
B	2	STA 5056	PROBABILITY AND STATISTICAL INFERENCE - II	COMPULSORY	3	0	0	9
B	3	STA 6098	PH.D. RESEARCH	COMPULSORY	3	0	0	9
B	0	-	ELECTIVE COURSE	ELECTIVE	-	-	-	7
TOTAL:								30

3 .Semester:
Semester	No	Course Unit Code	Course Unit Title	Course Unit Type	T	P	L	ECTS
G	1	STA 6094	PH.D. SEMINAR	COMPULSORY	0	3	0	5
G	2	STA 6098	PH.D. RESEARCH	COMPULSORY	3	0	0	9
G	0	-	ELECTIVE COURSE	ELECTIVE	-	-	-	16
TOTAL:								30

4 .Semester:
Semester	No	Course Unit Code	Course Unit Title	Course Unit Type	T	P	L	ECTS
B	1	STA 6099	PH.D. THESIS	COMPULSORY	0	0	0	30
TOTAL:								30

5 .Semester:
Semester	No	Course Unit Code	Course Unit Title	Course Unit Type	T	P	L	ECTS
G	1	STA 6099	PH.D. THESIS	COMPULSORY	0	0	0	30
TOTAL:								30

6 .Semester:
Semester	No	Course Unit Code	Course Unit Title	Course Unit Type	T	P	L	ECTS
B	1	STA 6099	PH.D. THESIS	COMPULSORY	0	0	0	30
TOTAL:								30

7 .Semester:
Semester	No	Course Unit Code	Course Unit Title	Course Unit Type	T	P	L	ECTS
G	1	STA 6099	PH.D. THESIS	COMPULSORY	0	0	0	30
TOTAL:								30

8 .Semester:
Semester	No	Course Unit Code	Course Unit Title	Course Unit Type	T	P	L	ECTS
B	1	STA 6099	PH.D. THESIS	COMPULSORY	0	0	0	30
TOTAL:								30

FLEXIBLE ELECTIVE COURSE ACCORDING TO ECTS
Semester	No	Course Unit Code	Course Unit Title	Course Unit Type	T	P	L	ECTS
Z	1	STA 5021	STATISTICAL SOFTWARE İN DATA ANALYSIS	ELECTIVE	2	2	0	7
Z	2	STA 6053	HEURISTIC SEARCH METHODS	ELECTIVE	3	0	0	5
Z	3	STA 5101	EXPLORATORY DATA ANALYSIS WITH R	ELECTIVE	3	0	0	8
Z	4	STA 5103	COMPUTATIONAL STATISTICS	ELECTIVE	3	0	0	8
Z	5	STA 5105	LINEAR TIME SERIES ANALYSIS	ELECTIVE	3	0	0	8
Z	6	STA 5107	META ANALYSIS	ELECTIVE	3	0	0	8
Z	7	STA 5031	LINEAR STATISTICAL MODELS	ELECTIVE	3	0	0	8
Z	8	STA 6013	ASYMPTOTIC THEORY FOR TIME SERIES	ELECTIVE	3	0	0	8
Z	9	STA 6009	ASSESSMENT OF INFLUENCE IN REGRESSION	ELECTIVE	3	0	0	8
Z	10	STA 5027	STATISTICAL DEPENDENCE AND COPULA THEORY IN FINANCE	ELECTIVE	3	0	0	7
Z	11	STA 5007	RESAMPLING METHODS	ELECTIVE	3	0	0	8
Z	12	STA 5009	SAMPLING AND SURVEY DESIGN	ELECTIVE	3	0	0	8
Z	13	STA 5015	STOCHASTIC PROCESSES	ELECTIVE	3	0	0	8
Z	14	STA 5013	TOTAL QUALITY MANAGEMENT AND AUDITING	ELECTIVE	3	0	0	7
Z	15	STA 5095	STATISTICAL PROCESS DESIGN AND IMPROVEMENT	ELECTIVE	3	0	0	7
Z	16	STA 6015	DATA MINING TECHNIQUES IN STATISTIC	ELECTIVE	3	0	0	8
Z	17	STA 5025	POWER ANALYSIS OF STATISTICAL METHODS	ELECTIVE	3	0	0	7
Z	18	STA 5023	CATEGORICAL DATA ANALYSIS	ELECTIVE	3	0	0	7
Z	19	STA 5109	RELIABILITY THEORY AND METHODS	ELECTIVE	3	0	0	8
Z	20	STA 6051	DYNAMIC PROGRAMMING	ELECTIVE	3	0	0	8
Z	21	STA 6045	LIFE CONTINGENCIES-I	ELECTIVE	3	0	0	8
Z	22	STA 6043	OPTIMIZATION THEORY	ELECTIVE	3	0	0	8
Z	23	STA 6011	MULTIVARIATE ANALYSIS	ELECTIVE	3	0	0	8
Z	24	STA 6007	ADVANCED SAMPLING THEORY	ELECTIVE	3	0	0	8
Z	25	STA 6003	ADVANCED PROBABILITY THEORY	ELECTIVE	3	0	0	8
Z	26	STA 6001	ADVANCED STATISTICAL INFERENCE - I	ELECTIVE	3	0	0	8
Z	27	STA 5093	MATHEMATICAL MODELING AND LINEAR OPTIMIZATION	ELECTIVE	3	0	0	7
Z	28	STA 5091	FINANCIAL MATHEMATICS	ELECTIVE	3	0	0	7
Z	29	STA 5083	DISCRETE OPTIMIZATION	ELECTIVE	3	0	0	7
Z	30	STA 5079	OPERATIONS RESEARCH IN LOGISTICS	ELECTIVE	3	0	0	7
Z	31	STA 5059	STATISTICAL RESEARCH METHODOLOGY I	ELECTIVE	3	0	0	7
Z	32	STA 5069	BIO-STATISTICS	ELECTIVE	3	0	0	7
Z	33	STA 5071	STATISTICAL QUALITY CONTROL	ELECTIVE	3	0	0	7
Z	34	STA 5075	REGRESSION ANALYSIS	ELECTIVE	3	0	0	7
Z	35	STA 5104	QUEUING THEORY	ELECTIVE	3	0	0	8
Z	36	STA 5054	NONPARAMETRIC STATISTICS	ELECTIVE	3	0	0	8
Z	37	STA 5090	SPECIAL TECHNIQUES IN QUALITY MANAGEMENT	ELECTIVE	3	0	0	8
Z	38	STA 5032	ADVANCED STATISTICAL QUALITY CONTROL	ELECTIVE	3	0	0	8
Z	39	STA 5110	SURVIVAL ANALYSIS	ELECTIVE	3	0	0	7
Z	40	STA 5108	ORDERED RANDOM VARIABLES	ELECTIVE	3	0	0	7
Z	41	STA 6004	ADVANCED EXPERIMENTAL DESIGN	ELECTIVE	3	0	0	8
Z	42	STA 5112	STATISTICAL METHODS IN MACHINE LEARNING	ELECTIVE	3	0	0	8
Z	43	STA 6002	ADVANCED STATISTICAL INFERENCE - II	ELECTIVE	3	0	0	9
Z	44	STA 5026	ROBUST ESTIMATION METHODS AND HYPOTHESIS TESTING	ELECTIVE	3	0	0	8
Z	45	STA 5094	LOSS MODELS	ELECTIVE	3	0	0	8
Z	46	STA 6016	SOFT COMPUTING TECHNOLOGIES	ELECTIVE	3	0	0	8
Z	47	STA 5024	ALTERNATIVE REGRESSION METHODS	ELECTIVE	3	0	0	8
Z	48	STA 5088	STATISTICAL SIMULATION	ELECTIVE	3	0	0	8
Z	49	STA 5086	INVENTORY THEORY	ELECTIVE	3	0	0	8
Z	50	STA 5084	NETWORK ANALYSIS	ELECTIVE	3	0	0	8
Z	51	STA 5012	NONLINEAR OPTIMIZATION	ELECTIVE	3	0	0	8
Z	52	STA 5082	GAME THEORY	ELECTIVE	3	0	0	8
Z	53	STA 6054	ADVANCED TIME SERIES ANALYSIS	ELECTIVE	3	0	0	8
Z	54	STA 5078	NONLINEAR TIME SERIES ANALYSIS	ELECTIVE	3	0	0	8
Z	55	STA 5106	GENERALIZED LINEAR MODELS	ELECTIVE	3	0	0	8
Z	56	STA 5074	SIX SIGMA IN QUALITY MANAGEMENT	ELECTIVE	2	2	0	8
Z	57	STA 6018	ADVANCED STOCHASTIC PROCESSES	ELECTIVE	3	0	0	8
Z	58	STA 5102	DECISION THEORY	ELECTIVE	3	0	0	8
Z	59	STA 5068	STATISTICAL DESIGN OF EXPERIMENTS	ELECTIVE	3	0	0	8
Z	60	STA 5060	STATISTICAL RESEARCH METHODOLOGY - II	ELECTIVE	3	0	0	8
Z	61	STA 6052	MATHEMATICAL RISK THEORY	ELECTIVE	3	0	0	8
Z	62	STA 5058	MULTIVARIATE STATISTICS	ELECTIVE	3	0	0	8
Z	63	STA 6046	LIFE CONTINGENCIES-II	ELECTIVE	3	0	0	8

Examination Regulations, Assessment and Grading

Related items of Dokuz Eylül University Regulations of Graduate Education and Exams and related items of Institute of Natural and Applied Sciences Regulations of Education and Code of Practicing Exams are applied for the exams and course grades. The course evaluation criteria are defined for each course by the instructor(s) of the corresponding course and are given in the Course Description Form found in the information package.

Graduation Requirements

Third Cycle (Doctor of Philosophy) Programme is comprised of courses (at least 67 ECTS),Ph.D.Seminar (5 ECTS), Ph. D. Research (18 ECTS) / Ph. D. Thesis (150 ECTS) courses, thesis proposal, doctoral qualifying examination and thesis examination with a total credit of 240 ECTS. Students must have minimum Cumulative Grade Point Average (CGPA) of 2.50 / 4.00 and completed all the courses with at least CB / S / TP grades.

Mode of Study (Full-Time, Part-Time, E-Learning )

Full-time

Programme Director or Equivalent

Head of Department:Prof.Dr.Burcu Hüdaverdi
E-mail : istatistik@deu.edu.tr
Telephone : +90 232 - 3018510
Dokuz Eylül Üniversitesi Fen Fakültesi
Tınaztepe Kampüsü
35390 Buca / İzmir

DEGREE PROGRAMMES