Third Cycle Programmes
    (Doctorate Degree)
Second Cycle Programmes
    (Master's Degree)
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    (Bachelor's Degree)
Short Cycle Programmes
    (Associate's Degree)
Second Cycle Programmes (Master's Degree)

Graduate School of Natural and Applied Sciences - Statistics - Second Cycle Programme with Thesis

General Description
The Department of Statistics is established as the seventh department of the Faculty of Science at Ege University and the department has begun undergraduate education between 1987 and 1988. Approximately 550 students in the department are educated by a scientific committee which consists of 17 members such as 2 professor, 5 assistant professor, 3 instructors and 7 assistants. The main objective of the department is to offer a well-balanced statistics program for prospective statisticians who may work in various fields including university teaching. The aim of the program offered by The Department of Statistics is two-fold: First is to provide its students with a firm foundation in the theory and application of the basic techniques of statistics; second is to ensure that students acquire a background knowledge in the other social sciences. The development of the student’s power of analytical reasoning is the major aim of the department.
Qualification Awarded
The Master’s Degree in Statistics (second cycle in Statistics) is awarded to the graduates who have successfully fulfilled all programme requirements
Second Cycle
Level of Qualification
Specific Admission Requirements
The applicants who hold a Bachelor's Degree and willing to enroll in the Master's programme may apply to the Directorate of the Graduate School with the documents: 1-Sufficient score (at least 55 out of 100) from the Academic Staff and Graduate Study Education Exam (ALES) conducted by Student Selection and Placement Center (OSYM) or GRE Graduate Record Examination (GRE) score or Graduate Management Admission Test (GMAT) score equivalent to ALES score of 55. 2-English proficiency (at least 70 out of 100 from the Profiency Exam conducted by Ege University Foreign Language Department, or at least 50 out of 100 from ÜDS (University Language Examination conducted by OSYM) or TOEFL or IELTS score equivalent to UDS score of 50. The candidates fulfilling the criteria outlined above are invited to interwiev. The assessment for admission to masters programs is based on : 50% of ALES, 25% of academic success in the undergraduate programme (cumulative grade point average (CGPA) ) and 25% of interview grade. The required minimum interview grade is 50 out of 100. The candidates having an assessed score of 60 at least are accepted into the Master's programme. The results of the evaluation are announced by the Directorate of Graduate School.
Specific Arrangements For Recognition Of Prior Learning (Formal, Non-Formal and Informal)
The rules for recognition of formal prior learning are well defined. A student who is currently enrolled in a Master's Degree programme in the same discipline at another institution and has successfully completed at least one semester, upon submitting all required documents before the deadline, may transfer to the Master's Programme at EGE University upon the recommendation of the department administration and with the approval of the Administrative Committee of the Graduate School. The decision taken will also include eligibility for exemption from some course requirements of the graduate program. Students who transfer from another university must be successful in the EGE University English Proficiency Exam or in an equivalent English examination. Recognition of prior non-formal and in-formal learning is at the beginning stage in Turkish Higher Education Institutions. Ege University is not an exception to this.
Qualification Requirements and Regulations
The programme consists of a minimum of seven courses delivered within the graduate programme of the department and in related fields, one seminar course, and thesis, with a minimum of 21 local credits. The seminar course and thesis are non-credit and graded on a pass/fail basis. The duration of the programme is four semesters. The maximum period to complete course work in a masters program with thesis is 4 semesters. However, with the approval of their advisors, students can in subsequent semesters take additional departmental courses with or without credits. The total ECTS credits of the programme is 120 ECTS. A student may take undergraduate courses on the condition that the courses have not been taken during the undergraduate program. However, at most two of these courses may be counted to the Master's course load and credits. Students must register for thesis work and the Specialization Field course offered by his supervisor every semester following the semester, in which the supervisor is appointed. A student who has completed work on the thesis within the time period, must write a thesis, using the data collected, according to the specifications of the Graduate School Thesis Writing Guide. The thesis must be defended in front of a jury. The Master's thesis jury is appointed on the recommendations of the relevant Department Chairperson and with the approval of the Administrative Committee of the Graduate School. The jury is composed of the thesis supervisor and 3 to 5 faculty members. Of the appointed jury members, up to one may be selected from another Department or another University. In case the jury consists of 3 members, the co-supervisor cannot be the jury member. A majority vote by the jury members determines the outcome of the thesis or examination. The vote can be for "acceptance", "rejection" or "correction". The Department Chairperson will inform the Director of the Graduate School, in writing, of the jury's decision within 3 days. To correct or change a thesis found incomplete and/or inadequate by the jury, the jury must specify in its report that such corrections are necessary. A student may be given, by a decision of the Administrative Committee of the Graduate School, up to three months to complete the corrections. The student must then retake the thesis examination.
Profile of The Programme
The student should pass courses of totally at least 21 credits in maximum 4 semesters. Then, student starts the thesis process which is planned to last 1 year. Student can take extension in time depending on his/her situation.
Occupational Profiles of Graduates With Examples
The graduates can work as an experiment organizer in planning units making quantitative analysis, in insurance companies, in various sectors in industry, in quality control departments, in stage of technology improvement, in research and consultancy companies, in the sectors about agriculture and industrial design. Therefore, they can employ in many public institutes in which evaluations are made such as State Planning Organization, Ministry of Industrial and Commerce, State Institute of Statistics, Institute of Standards, Employment Agency, in banks and in individual companies.
Access to Further Studies
Graduates who successfully completed the Master's Degree may apply to doctorate (third cycle) programmes in the same or in related disciplines.
Examination Regulations, Assessment and Grading
Students are required to take a mid-term examination and/or complete other assigned projects/homework during the semester and, additionally, are required to take a final examination and/or complete a final project for course evaluation. The final grade is based on the mid-term examination grade, the final examination grade and/or evaluation of final project, with the contributions of 40% and 60%, respectively. To pass any course, a Master's student must receive at least 70 out of 100. Students must repeat courses they have failed or may substitute courses the Department accepts as equivalent. The assessment for each course is described in detail in “Individual Course Description”.
Graduation Requirements
Mode of Study (Full-Time, Part-Time, E-Learning )
Address, Programme Director or Equivalent
Asst. Prof. Dr. Hakan Savas Sazak Ege University Faculty of Science Department of Statistics 35100 Bornova Izmir Turkey phone: +90 232 311 17 25 e-mail:
A laboratory of 13 computers for graduate students and a seminar room.

Key Learning Outcomes
1To be able to follow the Statistical Literature
2To be able to conduct detailed research on a specific area
3To be able to make an efficient presentation in a given time on a specific subject
4To be able to plan solution methods for a problem and be able to apply them
5To be able to use The Science of Statistics in multidisciplinary studies
6To be able to conduct intradisciplinary and multidisciplinary team studies
7To have scientific scepticism and verification skills
8To be able to communicate by expressing his/her ideas, written or orally in a clear and concise way
9The ability to think analytically
10To be able to conduct all the process in a scientific research including the definition of the problem, the design and reporting of the project, the collection, analysis and interpretation of the data with appropriate methods
11To have the initiative and individual working ability

Key Programme Learning Outcomes - NQF for HE in Turkey
TYYÇKey Learning Outcomes
COMPETENCES (Competence to Work Independently and Take Responsibility)1
COMPETENCES (Learning Competence)1
COMPETENCES (Communication and Social Competence)1
COMPETENCES (Field Specific Competence)1

Course Structure Diagram with Credits
T : Theoretical P: Practice L : Laboratory
1. Semester
No Course Unit Code Language of Instruction Course Unit Title Type of Course T P L ECTS
1 9101055052008 Turkish Advanced Mathematical Statistics Compulsory 3 0 0 8
2 İST-SG-YL-G ELECTIVE COURSES 1 Elective - - - 22
3 9101055332018 Scientific Research Methods and Ethics Compulsory 3 0 0 6
Total 6 0 0 36
2. Semester
No Course Unit Code Language of Instruction Course Unit Title Type of Course T P L ECTS
1 İST-SG-YL-B ELECTIVE COURSES 2 Elective - - - 24
2 FENYLSEM English Seminar Compulsory 0 0 0 6
Total 0 0 0 30
3. Semester
No Course Unit Code Language of Instruction Course Unit Title Type of Course T P L ECTS
1 YLUAD591 Turkish Specialization Field Compulsory 0 0 0 4
2 YLTEZ591 Turkish Thesis Study Compulsory 0 0 0 26
Total 0 0 0 30
4. Semester
No Course Unit Code Language of Instruction Course Unit Title Type of Course T P L ECTS
1 YLUAD591 Turkish Specialization Field Compulsory 0 0 0 4
2 YLTEZ592 Turkish Thesis Study Compulsory 0 0 0 26
Total 0 0 0 30
No Course Unit Code Language of Instruction Course Unit Title Type of Course T P L ECTS
1 9101055012007 Turkish Advanced Regression Analysis Elective 3 0 0 8
2 9101055032007 Turkish Statistical Quality Control and Applications Elective 3 0 0 7
3 9101055072010 Turkish Computer Based Statistics Elective 2 2 0 7
4 9101055092015 Turkish Statistical Reliability Analysis Elective 3 0 0 7
5 9101055112015 Turkish Fuzzy Logic and Probability Elective 3 0 0 7
6 9101055132015 Turkish Queueing Theory Elective 3 0 0 8
7 9101055192003 Turkish Econometric Methods Elective 3 0 0 8
8 9101055232006 Turkish Order Statistics Theory Elective 3 0 0 8
9 9101055252007 Turkish Statistical Computing Methods Elective 3 0 0 8
10 9101055312010 Turkish Time Series Analysis Elective 3 0 0 7
11 9101055412018 Statistical Methods in Validity and Reliability Analysis Elective 3 0 0 8
12 9101055432019 Taguchi’s Philosophy and Dual Response Surface Approaches Elective 3 0 0 8
No Course Unit Code Language of Instruction Course Unit Title Type of Course T P L ECTS
1 9101055022006 Turkish General Linear Models Elective 3 0 0 8
2 9101055042015 Turkish Biostatistics Elective 3 0 0 8
3 9101055062004 Turkish Multivariate Statistical Analysis Elective 3 0 0 8
4 9101055082015 Turkish Statistics For Engineering Elective 3 0 0 8
5 9101055102007 Turkish Sampling Theory Elective 3 0 0 8
6 9101055121998 Turkish Statistical Experimental Design Elective 3 0 0 8
7 9101055142015 Turkish System Simulation Elective 3 0 0 8
8 9101055262013 Turkish Probability and Statistics Elective 3 0 0 8
9 9101055282010 Turkish Statistical Simulation Elective 3 0 0 8
10 9101055342010 Turkish Nonparametric Statistics Elective 3 0 0 8
11 9101055402010 Turkish Advanced Process Control Techniques Elective 3 0 0 8
12 9101055422018 Turkish Categorical Data Analysis Elective 3 0 0 8
13 9101055462010 Turkish Nonlinear Optimization Problems Elective 3 0 0 8
Ege University, Bornova - İzmir / TURKEY • Phone: +90 232 311 10 10 • e-mail: