DEGREE PROGRAMMES

: STATISTICS (ENGLISH)

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

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:
Semester No Course Unit Code Course Unit Title Type of Course T P L ECTS
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