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's degree in Statistics , Master's degree in Statistics Scientific Preparation, Master's 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 aim of the program is to combine statistical theory and programming knowledge and skills for people who aim to pursue a career in fields such as Statistics, Data Science, Data Analytics, Machine Learning, Artificial Intelligence, Big Data, and to provide the necessary pre-knowledge in these fields and to prepare the infrastructure for doctoral programs. 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

M.Sc. in Statistics

Level of Qualification

Second Cycle (Master's Degree)

Specific Admission Requirements

First Cycle (Bachelor's Degree) diploma; minimum score of 55 from the National Central Graduate Education Entrance Examination (ALES) in the related field; a minimum score of 65 from the graduate school entrance exam;
For English proficiency; Minimum (65) points from the Foreign Language Proficiency Exam determined by the DEU School of Foreign Languages Practice Principles, or from the central foreign language exams YDS, e-YDS and YÖKDİL (English) or other foreign language exams whose equivalents are accepted by ÖSYM ( 60) points are required.

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

2 years (excluding one year of English Preparatory School), 2 semesters per year, 16 weeks per semester, 120 ECTS in total.

Profile of the Programme

The aim of the master 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 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 master 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 the ability of working independently
2	To evaluate any process and determine the variables describing or affecting the variation in the process
3	To collect data with correct methods
4	To estimate the probability distribution and parameters of the variables.
5	To compare the groups within the process.
6	To determine the cause and effect relation and to built the best model for this relation.
7	To optimize the process in terms of inputs and outputs.
8	To determine the risks within the process and decrease the losses
9	To be able to think multi-dimensional and to have the ability of consulting in a technical manner
10	To be very good at a foreing language, to have good communications skills and to be able to use information technologies professionally.

Occupational Profiles of Graduates with Examples

Our graduates can be employed at 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 third cycle programmes.

Course Structure Diagram with Credits

Semester	No	Course Unit Code	Course Unit Title	Type of Course	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 MAT 5102 NUMERICAL AND APPROXIMATE METHODS STA 5053 PROBABILITY AND STATISTICAL INFERENCE - I FBE 5557 SCIENTIFIC RESEARCH TECHNIQUES AND PUBLICATION ETHICS STA 5056 PROBABILITY AND STATISTICAL INFERENCE - II with approval of the supervisor. The registration must be noticed to the Institute during course registration period by the supervisor.
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	3	FBE 5557	SCIENTIFIC RESEARCH TECHNIQUES AND PUBLICATION ETHICS	COMPULSORY	3	0	0	5
G	0	-	ELECTIVE COURSE	ELECTIVE	-	-	-	8
TOTAL:								30

1 .Semester Elective:
Semester	No	Course Unit Code	Course Unit Title	Type of Course	T	P	L	ECTS
G	1	STA 5021	STATISTICAL SOFTWARE İN DATA ANALYSIS	ELECTIVE	2	2	0	7
G	2	STA 5109	RELIABILITY THEORY AND METHODS	ELECTIVE	3	0	0	8
G	3	STA 5069	BIO-STATISTICS	ELECTIVE	3	0	0	7
G	4	STA 5071	STATISTICAL QUALITY CONTROL	ELECTIVE	3	0	0	7
G	5	STA 5075	REGRESSION ANALYSIS	ELECTIVE	3	0	0	7
G	6	STA 5079	OPERATIONS RESEARCH IN LOGISTICS	ELECTIVE	3	0	0	7
G	7	STA 5083	DISCRETE OPTIMIZATION	ELECTIVE	3	0	0	7
G	8	STA 5091	FINANCIAL MATHEMATICS	ELECTIVE	3	0	0	7
G	9	STA 5093	MATHEMATICAL MODELING AND LINEAR OPTIMIZATION	ELECTIVE	3	0	0	7
G	10	STA 6001	ADVANCED STATISTICAL INFERENCE - I	ELECTIVE	3	0	0	8
G	11	STA 6003	ADVANCED PROBABILITY THEORY	ELECTIVE	3	0	0	8
G	12	STA 6007	ADVANCED SAMPLING THEORY	ELECTIVE	3	0	0	8
G	13	STA 6011	MULTIVARIATE ANALYSIS	ELECTIVE	3	0	0	8
G	14	STA 6043	OPTIMIZATION THEORY	ELECTIVE	3	0	0	8
G	15	STA 6045	LIFE CONTINGENCIES-I	ELECTIVE	3	0	0	8
G	16	STA 6051	DYNAMIC PROGRAMMING	ELECTIVE	3	0	0	8
G	17	STA 6053	HEURISTIC SEARCH METHODS	ELECTIVE	3	0	0	5
G	18	STA 5023	CATEGORICAL DATA ANALYSIS	ELECTIVE	3	0	0	7
G	19	STA 5025	POWER ANALYSIS OF STATISTICAL METHODS	ELECTIVE	3	0	0	7
G	20	STA 6015	DATA MINING TECHNIQUES IN STATISTIC	ELECTIVE	3	0	0	8
G	21	STA 5095	STATISTICAL PROCESS DESIGN AND IMPROVEMENT	ELECTIVE	3	0	0	7
G	22	STA 5013	TOTAL QUALITY MANAGEMENT AND AUDITING	ELECTIVE	3	0	0	7
G	23	STA 5015	STOCHASTIC PROCESSES	ELECTIVE	3	0	0	8
G	24	STA 5005	APPLIED STATISTICS IN SCIENTIFIC RESEARCH	ELECTIVE	4	0	0	7
G	25	STA 5009	SAMPLING AND SURVEY DESIGN	ELECTIVE	3	0	0	8
G	26	STA 5007	RESAMPLING METHODS	ELECTIVE	3	0	0	8
G	27	STA 5027	STATISTICAL DEPENDENCE AND COPULA THEORY IN FINANCE	ELECTIVE	3	0	0	7
G	28	STA 6009	ASSESSMENT OF INFLUENCE IN REGRESSION	ELECTIVE	3	0	0	8
G	29	STA 6013	ASYMPTOTIC THEORY FOR TIME SERIES	ELECTIVE	3	0	0	8
G	30	STA 5031	LINEAR STATISTICAL MODELS	ELECTIVE	3	0	0	8
G	31	STA 5107	META ANALYSIS	ELECTIVE	3	0	0	8
G	32	STA 5105	LINEAR TIME SERIES ANALYSIS	ELECTIVE	3	0	0	8
G	33	STA 5103	COMPUTATIONAL STATISTICS	ELECTIVE	3	0	0	8
G	34	STA 5101	EXPLORATORY DATA ANALYSIS WITH R	ELECTIVE	3	0	0	8
G	35	STA 5059	STATISTICAL RESEARCH METHODOLOGY I	ELECTIVE	3	0	0	7

2 .Semester:
Semester	No	Course Unit Code	Course Unit Title	Type of Course	T	P	L	ECTS
B	1	STA 5098	M.SC. RESEARCH	COMPULSORY	2	0	0	3
B	2	STA 5056	PROBABILITY AND STATISTICAL INFERENCE - II	COMPULSORY	3	0	0	9
B	3	STA 5096	M.SC. SEMINAR	COMPULSORY	0	2	0	3
B	0	-	ELECTIVE COURSE	ELECTIVE	-	-	-	15
TOTAL:								30

2 .Semester Elective:
Semester	No	Course Unit Code	Course Unit Title	Type of Course	T	P	L	ECTS
B	1	STA 5054	NONPARAMETRIC STATISTICS	ELECTIVE	3	0	0	8
B	2	STA 5112	STATISTICAL METHODS IN MACHINE LEARNING	ELECTIVE	3	0	0	8
B	3	STA 5060	STATISTICAL RESEARCH METHODOLOGY - II	ELECTIVE	3	0	0	8
B	4	STA 5068	STATISTICAL DESIGN OF EXPERIMENTS	ELECTIVE	3	0	0	8
B	5	STA 5074	SIX SIGMA IN QUALITY MANAGEMENT	ELECTIVE	2	2	0	8
B	6	STA 5078	NONLINEAR TIME SERIES ANALYSIS	ELECTIVE	3	0	0	8
B	7	STA 5082	GAME THEORY	ELECTIVE	3	0	0	8
B	8	STA 5084	NETWORK ANALYSIS	ELECTIVE	3	0	0	8
B	9	STA 5086	INVENTORY THEORY	ELECTIVE	3	0	0	8
B	10	STA 5088	STATISTICAL SIMULATION	ELECTIVE	3	0	0	8
B	11	STA 5094	LOSS MODELS	ELECTIVE	3	0	0	8
B	12	STA 6002	ADVANCED STATISTICAL INFERENCE - II	ELECTIVE	3	0	0	9
B	13	STA 6004	ADVANCED EXPERIMENTAL DESIGN	ELECTIVE	3	0	0	8
B	14	STA 6046	LIFE CONTINGENCIES-II	ELECTIVE	3	0	0	8
B	15	STA 6052	MATHEMATICAL RISK THEORY	ELECTIVE	3	0	0	8
B	16	STA 5012	NONLINEAR OPTIMIZATION	ELECTIVE	3	0	0	8
B	17	STA 5024	ALTERNATIVE REGRESSION METHODS	ELECTIVE	3	0	0	8
B	18	STA 6016	SOFT COMPUTING TECHNOLOGIES	ELECTIVE	3	0	0	8
B	19	STA 5026	ROBUST ESTIMATION METHODS AND HYPOTHESIS TESTING	ELECTIVE	3	0	0	8
B	20	STA 5032	ADVANCED STATISTICAL QUALITY CONTROL	ELECTIVE	3	0	0	8
B	21	STA 5090	SPECIAL TECHNIQUES IN QUALITY MANAGEMENT	ELECTIVE	3	0	0	8
B	22	STA 5104	QUEUING THEORY	ELECTIVE	3	0	0	8
B	23	STA 5102	DECISION THEORY	ELECTIVE	3	0	0	8
B	24	STA 6018	ADVANCED STOCHASTIC PROCESSES	ELECTIVE	3	0	0	8
B	25	STA 5106	GENERALIZED LINEAR MODELS	ELECTIVE	3	0	0	8
B	26	STA 6054	ADVANCED TIME SERIES ANALYSIS	ELECTIVE	3	0	0	8
B	27	STA 5108	ORDERED RANDOM VARIABLES	ELECTIVE	3	0	0	7
B	28	STA 5110	SURVIVAL ANALYSIS	ELECTIVE	3	0	0	7
B	29	STA 5058	MULTIVARIATE STATISTICS	ELECTIVE	3	0	0	8

3.Semester:
Semester	No	Course Unit Code	Course Unit Title	Type of Course	T	P	L	ECTS
G	1	STA 5099	M.SC. THESIS	COMPULSORY	0	0	0	30
TOTAL:								30

4.Semester:
Semester	No	Course Unit Code	Course Unit Title	Type of Course	T	P	L	ECTS
B	1	STA 5099	M.SC. THESIS	COMPULSORY	0	0	0	30
TOTAL:								30

Examination Regulations, Assessment and Grading

Related items of Dokuz Eylul 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

Second Cycle (Master's Degree) Programme with thesis is comprised of courses (at least 54 ECTS), a seminar (3 ECTS), M. Sc. Research (3 ECTS) and M. Sc. Thesis (60 ECTS), in total 120 ECTS credits. 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