DEGREE PROGRAMMES

: Statistics

General Description

History

The Department of Statistics, established under the Faculty of Arts and Sciences, started undergraduate and graduate education in the 1994-1995 academic year. In our department, besides the undergraduate, minor and double major programs, Masters's Degree in Statistics , Masters's Degree in Statistics (Scientific Preparation), Masters's Degree in Data Science (with and without Thesis), and Doctorate Degree in Statistics programs are carried out. 30% of the courses offered in undergraduate program are in English. Our department consists of six branches, such as Statistical Theory, Statistical Information Systems, Probability Theory and Processes, Risk Analysis, Applied Statistics and Operations Research.

Qualification Awarded

Statistics, Bachelor's Degree (B.Sc.)

Level of Qualification

First Cycle (Bachelor's Degree)

Specific Admission Requirements

High school diploma, placement through a nation-wide Student Selection Examination.

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

Item 12 of Dokuz Eylul University Associate and Bachelors Degree Education and Exam Regulations (dated 12 August 2011 published on the official gazette number 28023) is applied.
(1) The lateral transfers to the university are executed according to the principals that are determined by the Senate according to the Regulations on the Basis of Transfers between Institutions at Upper Secondary Education and Undergraduate level, Double Major, Minor and Transfer of Credits between Institutions published on official gazette dated 24/4/2010 numbered 27561.
(2) On vertical transfers, the regulations on the continuation of the graduates of Vocational School and Open Learning Secondary Education Program Graduates Bachelors Degree Education published on official gazette on 19/2/202 dated 24676 are applied.
(3) On transfers of students that have not or can not complete their bachelors degree education to the Vocational Schools, the regulations on awarding Upper Secondary Eduation Degree or adaptation to Vocational Schools for the students who have not completed or can not complete Bachelors Degree Education published on official gazette dated 18/3/1989 dated 20112 are applied.

Qualification Requirements and Regulations

Education is total 4 years with 2 semesters every year (excluding 1 year of prep class)
Grading is done on a 4 point system.
Students have to succeed in all courses. Evaluation of success on class : See: DEU Faulty of Science Education and Examination Application Rules, Items 25-27.
In order to graduate from the program, it is obligatory to do an internship for 32 (thirty-two) working days. (See Internship Directive)
3rd grade year students have to take 15 ECTS in the 5th semester and 15 ECTS in the 6th semester of departmental elective courses.
Students must take and succeed at least 4 ECTS Faculty Elective Course Pool in the 5th Semester or at least 4 ECTS University Elective Course Pool and at least 4 ECTS Faculty Elective Course Pool in the 6th Semester or at least 4 ECTS University Elective Course Pool.
4th grade students are required to take 10 ECTS in the 7th semester and 15 ECTS in the 8th semester of Departmental Elective Courses.
4th grade students must successfully complete a year-long graduation project.
Students must complete a minimum of 240 ECTS credits and have a minimum Cumulative Grade Point Average (C.G.P.A.) of 2.00/4.00 .
Detailed information can be accessed at the University and Faculty website.

Profile of the Programme

The aim of the undergraduate program of Department of Statistics is to equip students with theoretical and practical knowledge of statistics and assets that are required by decision makers having analytical and critical thinking skills. The program also aims to graduate students; who are aware of their responsibilities toward to the community and to their work; who can follow the developments on science and technology, and can renew the knowledge of statistics with the consciousness about lifelong learning.
Department offers Probability , Statistics, Calculus, Computational tools, Mathematical statistics, Statistical Inference, Linear Algebra and Computer programming courses during first two years. For the third year, the courses are mostly elective except Regression analysis, Linear programming, Financial Mathematics and Statistical Design of Experiments. During their fourth year students have to succeed in Multivariate Analysis, Nonparametric statistical Methods, and Time series Analysis courses. Other courses are elective. Department also offers lateral branch programme and double major programme. Moreover, we have bilateral agreement with various universities under ERASMUS and FARABI programs.

Key Learning Outcomes

1   Has the required level of mathematics and current software computer programming knowledge used in the data processing process within the field of statistics.
2   Uses theoretical and practical knowledge in the field to define problems, collects the necessary data within a plan, analyzes and interprets it. Develops alternative solutions based on evidence and research.
3   Takes responsibility with a creative and broad perspective, works effectively, and has the ability to use time efficiently, either individually or in interdisciplinary teams.
4   Plans and manages projects with analytical thinking ability.
5   Conducts resource research to access information, critically evaluates the acquired knowledge, and uses databases and other information sources.
6   With the awareness of the necessity of lifelong learning, follows developments in science and technology and has the competence to continuously renew oneself in the field.
7   Informs relevant individuals and institutions on issues related to the field of statistics and can communicate their thoughts and solutions to problems both in writing and orally.
8   With a sense of social responsibility, has the competence to organize and implement projects and activities for the social environment in which they live.
9   Uses the English language to follow knowledge in their field and communicate with colleagues.
10   Uses computer software and information-communication technologies required by the field of statistics.
11   Shares theoretical and technical knowledge in detail with experts in the field of statistics and at a basic level with those who are not experts in the field.
12   Holds societal, scientific, and ethical values in the stages of data collection, evaluation, interpretation, and dissemination of results related to their field.
13   Has sufficient awareness of social justice, quality culture, and the protection of cultural values, as well as environmental protection, occupational health, and safety in their work in the field.
14   Has sufficient infrastructure in theoretical and applied statistics, operations research, risk analysis, actuarial science, and areas where statistics is applied (biostatistics, finance, optimization, data mining, etc.).

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 second cycle programmes.

Course Structure Diagram with Credits

The program composed of core and elective courses. We have total elective courses; for Fall semester and the rest for the Spring semester. Moreover, there are different university and faculty elective courses available for whole faculty of science students. At least 8 ECTS of these courses have to be from university and faculty electives.
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 Course Unit Type T P L ECTS
G 1 ATA 1001 PRINCIPLES OF ATATURK AND HISTORY OF THE TURKISH REVOLUTION I REQUIRED 2 0 0 2
G 2 FSH 0001 COMMUNICATION SKILLS REQUIRED 2 0 0 2
G 3 Ä°ST 1013 PROBABILITY I REQUIRED 2 0 0 4
G 4 Ä°ST 1015 STATISTIC I REQUIRED 4 0 0 7
G 5 Ä°ST 1051 COMPUTATIONAL TOOLS FOR STATISTICS I REQUIRED 2 0 0 4
G 6 Ä°ST 1095 TECHNICAL ENGLISH I REQUIRED 2 0 0 2
G 7 KPD 1000 CAREER PLANNING REQUIRED 1 0 0 2
G 8 MAT 1001 CALCULUS I REQUIRED 4 0 0 5
G 9 TDL 1001 TURKISH LANGUAGE I REQUIRED 2 0 0 2
G 0 - ELECTIVE COURSE ELECTIVE - - - 0
TOTAL:   30
 
2. Semester:
Semester No Course Unit Code Course Unit Title Course Unit Type T P L ECTS
B 1 ATA 1002 PRINCIPLES OF ATATURK AND HISTORY OF THE TURKISH REVOLUTION II REQUIRED 2 0 0 2
B 2 FSH 0002 PROFESSIONAL VALUES AND ETHICS REQUIRED 2 0 0 2
B 3 Ä°ST 1014 PROBABILITY II REQUIRED 2 0 0 4
B 4 Ä°ST 1016 STATISTICS II REQUIRED 4 0 0 7
B 5 Ä°ST 1052 COMPUTATIONAL TOOLS FOR STATISTIS II REQUIRED 2 0 0 3
B 6 Ä°ST 1094 TECHNICAL ENGLISH II REQUIRED 2 0 0 3
B 7 MAT 1002 CALCULUS II REQUIRED 4 0 0 5
B 8 TDL 1002 TURKISH LANGUAGE II REQUIRED 2 0 0 2
B 0 - ELECTIVE COURSE ELECTIVE - - - 2
TOTAL:   30
 
2 .Semester: Elective Course
Semester No Course Unit Code Course Unit Title Course Unit Type T P L ECTS
B 1 BDE 1003 PHYSICAL EDUCATION ELECTIVE 2 0 0 2
B 2 GSH 1003 FOLK DANCING ELECTIVE 2 0 0 2
B 3 GSM 1003 MUSIC ELECTIVE 2 0 0 2
B 4 GSR 1003 PAINTING ELECTIVE 2 0 0 2
 
3 .Semester:
Semester No Course Unit Code Course Unit Title Course Unit Type T P L ECTS
G 1 BÄ°L 2205 COMPUTER PROGRAMMING I REQUIRED 2 2 0 6
G 2 Ä°ST 2015 PROBLEM BASED LEARNING I REQUIRED 2 0 0 4
G 3 Ä°ST 2017 MATHEMATICAL STATISTICS REQUIRED 4 0 0 7
G 4 Ä°ST 2065 STATISTICAL QUALITY CONTROL REQUIRED 2 2 0 6
G 5 MAT 2001 INTRODUCTION TO LINEAR ALGEBRA REQUIRED 4 0 0 7
G 0 - ELECTIVE COURSE ELECTIVE - - - 0
TOTAL:   30
 
4. Semester:
Semester No Course Unit Code Course Unit Title Course Unit Type T P L ECTS
B 1 Ä°ST 2016 PROBLEM BASED LEARNING II REQUIRED 2 0 0 4
B 2 Ä°ST 2018 STATISTICAL INFERENCE REQUIRED 4 0 0 7
B 3 Ä°ST 2038 SAMPLING METHODS REQUIRED 2 2 0 7
B 4 Ä°ST 2050 R STATISTICAL PROGRAMMING LANGUAGE REQUIRED 2 2 0 6
B 5 MAT 2026 LINEAR ALGEBRA REQUIRED 4 0 0 6
B 0 - ELECTIVE COURSE ELECTIVE - - - 0
TOTAL:   30
 
5 .Semester:
Semester No Course Unit Code Course Unit Title Course Unit Type T P L ECTS
G 1 Ä°ST 3031 REGRESSION ANALYSIS REQUIRED 4 0 0 6
G 2 Ä°ST 3075 LINEAR PROGRAMMING REQUIRED 2 2 0 5
G 0 - ELECTIVE COURSE ELECTIVE - - - 19
TOTAL:   30
 
5 .Semester: Elective Course
Semester No Course Unit Code Course Unit Title Course Unit Type T P L ECTS
G 1 BÄ°L 3203 DATABASE MANAGEMENT ELECTIVE 3 0 0 5
G 2 Ä°ST 3103 GUIDED GROUP STUDY I ELECTIVE 3 0 0 5
G 3 Ä°ST 3113 EVERYDAY PROBABILITY AND STATISTICS ELECTIVE 3 0 0 5
G 4 Ä°ST 3119 ORDER STATISTICS AND ITS APPLICATIONS ELECTIVE 3 0 0 5
G 5 Ä°ST 3121 INTRODUCTION TO INFORMATION THEORY ELECTIVE 3 0 0 5
G 6 Ä°ST 3131 SIMULATION METHODS IN STATISTICS ELECTIVE 3 0 0 5
G 7 Ä°ST 3163 QUALITY ASSURANCE SYSTEMS AND CONTROL ELECTIVE 3 0 0 5
G 8 Ä°ST 3165 BUSINESS PROCESS IMPROVEMENT ELECTIVE 3 0 0 5
G 9 Ä°ST 3167 BIOSTATISTICS ELECTIVE 3 0 0 5
G 10 Ä°ST 3169 TOTAL QUALITY MANAGEMENET ELECTIVE 3 0 0 5
G 11 Ä°ST 3175 DECISION THEORY ELECTIVE 3 0 0 5
G 12 Ä°ST 3177 SURVEY DESIGN AND EXPERIMENT ELECTIVE 3 0 0 5
 
6. Semester:
Semester No Course Unit Code Course Unit Title Course Unit Type T P L ECTS
B 1 Ä°ST 3002 FINANCIAL MATHEMATICS REQUIRED 2 2 0 5
B 2 Ä°ST 3032 STATISTICAL DESIGN OF EXPERIMENT REQUIRED 4 0 0 6
B 0 - ELECTIVE COURSE ELECTIVE - - - 19
TOTAL:   30
 
6 .Semester: Elective Course
Semester No Course Unit Code Course Unit Title Course Unit Type T P L ECTS
B 1 BÄ°L 3120 COMPUTER PROGRAMMING II ELECTIVE 3 0 0 5
B 2 Ä°ST 3104 GUIDED GROUP STUDY II ELECTIVE 3 0 0 5
B 3 Ä°ST 3108 DATA ANALYSIS AND GRAPHICS USING R ELECTIVE 3 0 0 5
B 4 Ä°ST 3114 INTRODUCTION TO BAYESIAN STATISTICS ELECTIVE 3 0 0 5
B 5 Ä°ST 3132 SPECIAL TOPICS IN REGRESSION ANALYSIS ELECTIVE 3 0 0 5
B 6 Ä°ST 3134 ECONOMETRIC METHODS ELECTIVE 3 0 0 5
B 7 Ä°ST 3138 TIME SERIES REGRESSION ELECTIVE 3 0 0 5
B 8 Ä°ST 3162 SPECIAL METHODS IN QUALITY TECHNIQUES ELECTIVE 3 0 0 5
B 9 Ä°ST 3164 SIX SIGMA METHODOLOGY ELECTIVE 3 0 0 5
B 10 Ä°ST 3166 STATISTICAL METHODS IN CLINICAL TRIALS ELECTIVE 3 0 0 5
B 11 Ä°ST 3176 OPERATION RESEARCH ELECTIVE 3 0 0 5
B 12 Ä°ST 3178 INVENTORY MANAGEMENT ELECTIVE 3 0 0 5
 
7 .Semester:
Semester No Course Unit Code Course Unit Title Course Unit Type T P L ECTS
G 1 Ä°ST 4001 GRADUATION PROJECT REQUIRED 2 0 0 8
G 2 Ä°ST 4035 NONPARAMETRIC STATISTICAL METHODS REQUIRED 2 2 0 6
G 3 Ä°ST 4037 MULTIVARIATE STATISTICAL ANALYSIS REQUIRED 2 2 0 6
G 0 - ELECTIVE COURSE ELECTIVE - - - 10
TOTAL:   30
 
7 .Semester: Elective Course
Semester No Course Unit Code Course Unit Title Course Unit Type T P L ECTS
G 1 Ä°ST 4113 STOCHASTIC PROCESSES ELECTIVE 3 0 0 5
G 2 Ä°ST 4117 INTRODUCTION TO ROBUST ESTIMATION AND INFERENCE ELECTIVE 3 0 0 5
G 3 Ä°ST 4141 FINANCIAL TIME SERIES ANALYSIS ELECTIVE 3 0 0 5
G 4 Ä°ST 4143 RELIABILITY AND LIFETIME ANALYSIS ELECTIVE 3 0 0 5
G 5 Ä°ST 4155 DATA MANAGEMENT IN STATISTICS WITH EXCEL ELECTIVE 3 0 0 5
G 6 Ä°ST 4161 ADVANCED STATISTICAL QUALITY CONTROL ELECTIVE 3 0 0 5
G 7 Ä°ST 4175 NETWORK ANALYSIS ELECTIVE 3 0 0 5
G 8 Ä°ST 4181 LIFE INSURANCE ELECTIVE 3 0 0 5
 
8. Semester:
Semester No Course Unit Code Course Unit Title Course Unit Type T P L ECTS
B 1 Ä°ST 4040 TIME SERIES ANALYSIS REQUIRED 2 2 0 7
B 2 Ä°ST 4200 INTERNSHIP SUMMER TRAINING 0 0 0 8
B 0 - ELECTIVE COURSE ELECTIVE - - - 15
TOTAL:   30
 
8 .Semester: Elective Course
Semester No Course Unit Code Course Unit Title Course Unit Type T P L ECTS
B 1 Ä°ST 4102 APPLICATION OF RESAMPLING METHODS WITH R ELECTIVE 3 0 0 5
B 2 Ä°ST 4112 PROBABILITY IN RISK ANALYSIS ELECTIVE 3 0 0 5
B 3 Ä°ST 4138 STATISTICAL METHODS IN DATA MINING ELECTIVE 3 0 0 5
B 4 Ä°ST 4154 WEB BASED SURVEY ELECTIVE 3 0 0 5
B 5 Ä°ST 4164 STATISTICAL PROCESS MONITORING AND CONTROL TECHNIQUES ELECTIVE 3 0 0 5
B 6 Ä°ST 4176 QUEUING THEORY ELECTIVE 3 0 0 5
B 7 Ä°ST 4182 INTRODUCTION TO ACTUARIAL MODELS ELECTIVE 3 0 0 5
B 8 Ä°ST 4184 STATISTICS IN RISK MANAGMENT ELECTIVE 3 0 0 5
B 9 Ä°ST 4186 ROBUST ANALYSIS OF VARIANCE METHODS ELECTIVE 3 0 0 5
B 10 Ä°ST 4188 CATEGORICAL DATA ANALYSIS ELECTIVE 3 0 0 5
 
 
FLEXIBLE ELECTIVE COURSE ACCORDING TO ECTS
Semester No Course Unit Code Course Unit Title Course Unit Type T P L ECTS
H 1 GÇD 1000 VOLUNTEERISM STUDIES FACULTY ELECTIVE COURSE 1 2 0 4
H 1 MTH 0001 BLOCKCHAIN TECHNOLOGY AND ITS APPLICATIONS FACULTY ELECTIVE COURSE 2 0 0 2
H 2 MTH 0002 INSTRUMENTAL ANALYSIS-CHROMATOGRAPHY FACULTY ELECTIVE COURSE 2 0 0 2
H 3 MTH 0003 HYDROGEN FUEL CELL TECHNOLOGY FACULTY ELECTIVE COURSE 2 0 0 2
H 4 MTH 0004 MEDICAL POLYMERS FACULTY ELECTIVE COURSE 3 0 0 3
H 5 MTH 0005 PRODUCING OPEN SOFTWARE FACULTY ELECTIVE COURSE 2 0 0 2
H 6 MTH 0006 INTRODUCTION TO STATISTICS AND DATA SCIENCE FACULTY ELECTIVE COURSE 2 0 0 2
H 7 MTH 0007 BIG DATA TECHNOLOGIES FACULTY ELECTIVE COURSE 2 0 0 2
H 8 MTH 0008 MEDICAL METROLOGY AND ULTRASONIC APPLICATIONS FACULTY ELECTIVE COURSE 2 0 0 2
H 1 ERA 0001 SOFT COMPUTING TECHNIQUES ERASMUS 2 2 0 5
H 2 ERA 0002 SOFTWARE PROJECT MANAGEMENT ERASMUS 3 0 0 5
H 3 ERA 0003 BIOLOGICAL IMPACTS OF CLIMATE CHANGE ERASMUS 3 0 0 6
H 4 ERA 0004 HUMAN ANATOMY AND PHYSIOLOGY ERASMUS 2 0 0 6
H 5 ERA 0005 QUANTUM PHYSICS FOR EVERYONE ERASMUS 2 2 0 7
H 6 ERA 0006 DARK MATTER AND MYSTERIOUS OF THE UNIVERSE-I ERASMUS 2 2 0 7
H 7 ERA 0007 TIME SERIES MODELS ERASMUS 4 0 0 6
H 8 ERA 0008 ESTIMATION AND HYPOTHESIS TESTING ERASMUS 4 0 0 6
H 9 ERA 0009 DISCRETE MATHEMATICS AND ITS APPLICATIONS ERASMUS 3 0 0 5
H 10 ERA 0010 PROOF TECHNIQUES ERASMUS 2 0 0 2
H 11 ERA 0011 UNDERSTANDING LIFE WITH CODES AND THEIR READINGS ERASMUS 3 0 0 5
H 12 ERA 0012 MATERIAL CHEMISTRY ERASMUS 3 0 0 6
H 13 ERA 0013 NANOMATERIALS AND MEDICAL APPLICATIONS ERASMUS 3 0 0 6
H 14 ERA 0014 HISTORY OF MATHEMATICAL THOUGHT ERASMUS 2 0 0 2
H 15 ERA 0015 INTRODUCTION TO MOBILE PROGRAMMING ERASMUS 2 2 0 5
H 16 FSH 0004 PHILOSOPHY OF SCIENCE FACULTY ELECTIVE COURSE 2 0 0 2
H 17 FSH 0006 HISTORY OF SCIENCE FACULTY ELECTIVE COURSE 2 0 0 2
H 18 FSH 0007 SOLUTION OF INTERPERSONAL CONFLICTS FACULTY ELECTIVE COURSE 2 0 0 2
H 19 FSH 0008 SCIENCE IN DAILY LIFE FACULTY ELECTIVE COURSE 2 0 0 2
H 20 FSH 0011 CREATIVITY, RD, Ä°NNOVATION FACULTY ELECTIVE COURSE 2 0 0 2
H 21 FSH 0012 FUTURE PLANNING AND STRATEGY FACULTY ELECTIVE COURSE 2 0 0 2
H 22 FSH 0013 YOUTH ENTREPRENEURSHIP FACULTY ELECTIVE COURSE 2 0 0 2
H 23 FSH 0015 GLOBALIZATION AND THE NEW WORLD ORDER FACULTY ELECTIVE COURSE 2 0 0 2
H 24 FSH 0020 MANAGEMENT FACULTY ELECTIVE COURSE 2 0 0 2
H 25 FSH 0021 ECONOMICS FACULTY ELECTIVE COURSE 2 0 0 2
H 26 FSH 0022 ACCOUNTING FACULTY ELECTIVE COURSE 2 0 0 2
H 27 FSH 0023 MARKETING FACULTY ELECTIVE COURSE 2 0 0 2
H 28 FSH 0024 BASIC LAW FACULTY ELECTIVE COURSE 2 0 0 2
H 29 FSH 0025 MONEY AND BANKING FACULTY ELECTIVE COURSE 2 0 0 2
H 30 FSH 0026 TOTAL QUALITY AND ACCREDITATION FACULTY ELECTIVE COURSE 2 0 0 2
H 31 FSH 0028 FLOWERING PLANTS, NATURE'S HEALING HANDS FACULTY ELECTIVE COURSE 2 0 0 2
H 32 FSH 0029 BASIC BANKING AND INFORMATION TECHNOLOGIES FACULTY ELECTIVE COURSE 2 0 0 2
H 33 FSH 0031 TRANSLATION FACULTY ELECTIVE COURSE 2 0 0 2
H 34 FSH 0032 TEXT ANALYSIS FACULTY ELECTIVE COURSE 2 0 0 2
H 35 FSH 0033 SEMANTICS FACULTY ELECTIVE COURSE 2 0 0 2
H 36 FSH 0034 TERMINOLOGY AND TERMINOGRAPHY FACULTY ELECTIVE COURSE 2 0 0 2
H 37 FSH 0035 FINANCIAL ECONOMICS FACULTY ELECTIVE COURSE 2 0 0 2
H 38 FSH 0036 ECONOMIC GLOBALIZATION FACULTY ELECTIVE COURSE 2 0 0 2
H 39 FSH 0040 CHEMISTRY AND ART FACULTY ELECTIVE COURSE 2 0 0 2
H 40 FSH 0041 QUANTUM ERA FACULTY ELECTIVE COURSE 2 0 0 2
H 41 FSH 0042 BASIC STATISTICS FACULTY ELECTIVE COURSE 2 0 0 2
H 42 FSH 0043 REFLECTIONS ON MODERNLIFE FACULTY ELECTIVE COURSE 2 0 0 2
H 43 FSH 0044 SCIENTIFIC WRITING WITH LATEX FACULTY ELECTIVE COURSE 2 0 0 2
H 44 FSH 0045 INTRODUCTION TO PROGRAMMING WITH PYTHON FACULTY ELECTIVE COURSE 2 0 0 2
H 45 FSH 0046 ZOOGEOGRAPHY FACULTY ELECTIVE COURSE 2 0 0 2
H 46 FSH 0047 CREATING REPORTS AND PRESENTATIONS BY OFFICE PROGRAMS FACULTY ELECTIVE COURSE 2 0 0 2
H 47 FSH 0048 EXCEL FOR BUSINESS WORLD FACULTY ELECTIVE COURSE 2 0 0 2
H 48 FSH 0049 BIOLOGICAL IMPACTS OF CLIMATE CHANGE FACULTY ELECTIVE COURSE 2 0 0 2
H 49 FSH 0050 PIONEERS OF SCIENCE FACULTY ELECTIVE COURSE 3 0 0 5
H 50 FSH 0051 HEALTH KNOWLEDGE AND FIRST AID FACULTY ELECTIVE COURSE 2 0 0 4
H 51 FSH 0052 REPTILE AND AMPHIBIAN DIVERSITY OF TüRKIYE FACULTY ELECTIVE COURSE 2 0 0 4
H 52 FSH 0053 PROJECT PROPOSAL PREPARATION FACULTY ELECTIVE COURSE 2 0 0 2
H 53 FSH 0054 DATA PREPROCESSING FACULTY ELECTIVE COURSE 2 0 0 2
H 54 FSH 0055 MEDICAL IMAGING SYSTEMS FACULTY ELECTIVE COURSE 2 0 0 2
H 55 FSH 0056 ENVIRONMENTAL RADIOACTIVITY FACULTY ELECTIVE COURSE 2 0 0 2
H 56 FSH 0057 ARTIFICIAL INTELLIGENCE WITH APPLICATIONS FACULTY ELECTIVE COURSE 0 2 0 2
H 57 Ä°HD 1001 HUMAN RIGHTS FACULTY ELECTIVE COURSE 2 0 0 4
 

Examination Regulations, Assessment and Grading

Related items of Dokuz Eylul University Associate and Bachelors Degree and Faculty of Science Education and Exam Regulations are applied. See the following links for these regulations.

Graduation Requirements

Education is total 4 years with 2 semesters every year (excluding 1 year of prep class)
Grading is done on a 4 point system.
Students have to succeed in all courses. Evaluation of success on class : See: DEU Faulty of Science Education and Examination Application Rules, Items 25-27.
In order to graduate from the program, it is obligatory to do an internship for 32 (thirty-two) working days. (See Internship Directive)
3rd grade year students have to take 15 ECTS in the 5th semester and 15 ECTS in the 6th semester of departmental elective courses.
Students must take and succeed at least 4 ECTS Faculty Elective Course Pool in the 5th Semester or at least 4 ECTS University Elective Course Pool and at least 4 ECTS Faculty Elective Course Pool in the 6th Semester or at least 4 ECTS University Elective Course Pool.
4th grade students are required to take 10 ECTS in the 7th semester and 15 ECTS in the 8th semester of Departmental Elective Courses.
4th grade students must successfully complete a year-long graduation project.
Students must complete a minimum of 240 ECTS credits.
Minimum graduation grade 2.00 / 4.00.

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

Full-time

Programme Director or Equivalent

e-mail: istatistik@deu.edu.tr;
Tel: (232) 301 85 09