Türkçe
Graduate School Of Natural And Applied Sciences Statistics

Qualification Awarded

Master of Science Degree

Specific Admission Requirements

1) Having an undergraduate degree from a national university or from an abroad university the degree of which is accepted by YÖK (Council of Higher Education) 2) Having a standard score of at least 55 from ALES or at least an equivalent score from the exams recognized by council of inter university

Qualification Requirements

The programme consists of a minimum of 7 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. 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.

Recognition of Prior Learning

Recognition of prior learning is at the beginning stage in the Turkish Higher Education System. Mugla Sıtkı Koçman University and hence the Department of Statistics is no exception to this. However, exams of exemption are organised at the start of each term at the University for courses compulsory in the curriculum, such as Foreign Languages and Basic Computing. The students who have completed the learning process for these courses on his/her own or through other means, and believe that they have achieved the learning outcomes specified are given the right to take the exemption exam. The students who achieve a passing grade from these exams are held exempt from the related course in the curriculum, and this grade is entered into the transcript of the student.

History

The Department of Statistics and Computer Science was founded as a major within the Faculty of Arts and Science in 1994. The department turned into Statistics Depertment in 2007. There are two formal education programs in the Department of Statistics, primary and secondary education. Moreover, there is also Master's program in our Department.

Profile of the Programme

The Department of Statistics offers graduate courses to its own graduate students and to graduate students in other departments. In the Statistics Department the work done on theses is based on research. Depending on the topic selected, the thesis topic could involve research into linear and nonlinear models, econometry, biostatistics, statistical quality control, regression, experimental designs, multivariate statistical analysis, fuzzy anlaysis.

Program Outcomes

1- To develop one's knowledge about statistical theory and its applications at the proficiency level based on competencies of undergraduate level
2- To be able to use the acquired advanced level of knowledge in the fields of theoretical and applied statistics
3- To be able to identify problems, analyze them and produce solutions based on scientific methods
4- To be able to apply methods of theoretical and applied statistics in real life by an interdisciplinary approach
5- To be able to conduct an study which needs some expertise in the fields where statistical methods are used
6- To be able to assess cricitically advanced level knowledge and skills gained in applied statistics
7- To be able to communicate easily theoretical and technical knowledge with the relevant people
8- To be able to use national and international academic references
9- To have knowledge and experience about the software packages commonly used in statistics
10- To be able to design methods of solution specific to problem and use appropriate tools in doing so.
11- To take responsibility as a individual or a member of team in the applied and theoretical studies

Exam Regulations & Assesment & Grading

The Master Degree programme consists of a minimum of seven courses, with a minimum of 21 national credits. Each course is assessed via a midterm exam and a final end-of-term exam, with contributions of 40%, 60% respectively. Student must achieve a CGPA of at least 2.5 out of 4.00 and prepared and successfully defended a thesis are given Master Degree in the field of Mathematics.

Graduation Requirements

The Master Degree programme consists of a minimum of seven courses, with a minimum of 21 national credits, a qualifying examination, a dissertation proposal, and a dissertation. The seminar course and thesis are non-credit and graded on a pass/fail basis. The total ECTS credits of the programme is 240 ECTS. 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.

Occupational Profiles of Graduates

If the graduates have formation and get KPSS Marks, they can be appointed as statisticians or civil servant sin government institutions. The graduatues also can find jobs in financial institutions such as banks. On computer sector they can work in diferent positions. The students who are in graduate education can be researcher and researcher assistants in universities.

Access to Further Studies

Graduates who succesfully completed Master degree may apply to both in the same or related disciplines in higher education institutions at home or abroad to get a position in academic staff or to governmental R&D centres to get expert position.

Mode of Study

Graduate Education

Programme Director

Associate Prof.Dr. Dursun AYDIN

ECTS Coordinator

Associate Prof.Dr. Atilla GÖKTAŞ

Course Structure Diagram with Credits

1. Year - 1. Term
Course Unit Code Course Unit Title Course Type Theory Practice ECTS Print
İST5090 Seminar Required 0 2 6
İST5099 Scientific Research Techniques and Publishing Ethics Required 3 0 6
İST5501 ACTUARIAL ANALYSIS AND RISK THEORY Elective 3 0 6
İST5503 EPISTEMOLOGY Elective 3 0 6
İST5505 GOAL PROGRAMMING Elective 3 0 6
İST5507 RESISTANT STATISTICAL METHODS Elective 3 0 6
İST5509 LINEAR MODELS THEORY Elective 3 0 6
İST5511 ECONOMETRIC MODELS Elective 3 0 6
İST5513 EFFICIENCY ANALYSIS Elective 3 0 6
İST5515 GENERAL LINEAR MODELS Elective 3 0 6
İST5517 GENETIC ALGORITHM Elective 3 0 6
İST5519 GRAPHIC MODELS Elective 3 0 6
İST5521 ADVANCED BAYESIAN APPROACHES Elective 3 0 6
İST5523 STATISTICAL DISPERSION THEORY Elective 3 0 6
İST5525 STATISTICAL SOFTWARE AND DATA ANALYSIS Elective 3 0 6
İST5527 CATEGORICAL DATA ANALYSIS Elective 3 0 6
İST5529 PROBABILITY THEORY Elective 3 0 6
İST5531 SAMPLING THEORY Elective 3 0 6
İST5533 NONPARAMETRIC STATISTICAL METHODS Elective 3 0 6
İST5535 REGRESSION THEORY Elective 3 0 6
İST5537 VARIATE PROCESSES Elective 3 0 6
İST5539 VARIANCE ANALYSIS Elective 3 0 6
İST5541 ARTIFICIAL NEURAL NETWORKS Elective 3 0 6
İST5543 SOFTWARE QUALITY ASSURANCE Elective 3 0 6
İST5545 TIME SERIES ANALYSIS Elective 3 0 6
İST5701 Specialization Field Course Required 4 0 6
       
1. Year - 2. Term
Course Unit Code Course Unit Title Course Type Theory Practice ECTS Print
İST5502 SIMULATION TECHNIQUES AND MODELLING Elective 3 0 6
İST5504 FUZZY LOGIC Elective 3 0 6
İST5506 MULTIVARIATE STATISTICAL METHODS Elective 3 0 6
İST5508 DESIGNING AN EXPERIMENT Elective 3 0 6
İST5510 LINEAR PROGRAMMING Elective 3 0 6
İST5512 SOFT COMPUTING METHODS Elective 3 0 6
İST5514 APPLIED STATISTICS IN NATURAL AND SOCIAL SCIENCES Elective 3 0 6
İST5516 GENERALISED LINEAR MODELS Elective 3 0 6
İST5518 GRAPH THEORY AND APPLICATIONS Elective 3 0 6
İST5520 HYPOTHESIS TESTS Elective 3 0 6
İST5522 STATISTIC THEORY Elective 3 0 6
İST5524 STATISTICAL QUALITY CONTROL Elective 3 0 6
İST5526 DECISION-MAKING AND GAME THEORY Elective 3 0 6
İST5528 MATHEMATICAL STATISTICS Elective 3 0 6
İST5530 OPTIMIZATION Elective 3 0 6
İST5532 PANEL DATA ANALYSIS Elective 3 0 6
İST5534 POPULATION GENETICS Elective 3 0 6
İST5536 SUBSTANTIAL DATA ANALYSIS Elective 3 0 6
İST5538 INTEGER PROGRAMMING Elective 3 0 6
İST5540 DATA MINING Elective 3 0 6
İST5542 VITAL ANALYSIS Elective 3 0 6
İST5544 OPERATIONAL RESEARCH Elective 3 0 6
İST5702 Specialization Field Course Required 4 0 6
       
2. Year - 1. Term
Course Unit Code Course Unit Title Course Type Theory Practice ECTS Print
İST5000 Thesis Work Required 0 0 24
İST5703 Specialization Field Course Required 4 0 6
       
2. Year - 2. Term
Course Unit Code Course Unit Title Course Type Theory Practice ECTS Print
İST5704 Specialization Field Course Required 4 0 6
       
 

Evaluation Questionnaires

Course & Program Outcomes Matrix

1. Year - 1. Term
Ders AdıPy1Py2Py3Py4Py5Py6Py7Py8Py9Py10Py11
Seminar           
Scientific Research Techniques and Publishing Ethics           
ACTUARIAL ANALYSIS AND RISK THEORY35435544354
EPISTEMOLOGY44524533543
GOAL PROGRAMMING54353525524
RESISTANT STATISTICAL METHODS42535425543
LINEAR MODELS THEORY42545344555
ECONOMETRIC MODELS54543545335
EFFICIENCY ANALYSIS35243543545
GENERAL LINEAR MODELS54535534553
GENETIC ALGORITHM53435434554
GRAPHIC MODELS45354545345
ADVANCED BAYESIAN APPROACHES35545254345
STATISTICAL DISPERSION THEORY43435432453
STATISTICAL SOFTWARE AND DATA ANALYSIS45352544525
CATEGORICAL DATA ANALYSIS35243543545
PROBABILITY THEORY45353452455
SAMPLING THEORY35243543545
NONPARAMETRIC STATISTICAL METHODS53453355455
REGRESSION THEORY54434535344
VARIATE PROCESSES45353452455
VARIANCE ANALYSIS35445345334
ARTIFICIAL NEURAL NETWORKS5354 355435
SOFTWARE QUALITY ASSURANCE45354452435
TIME SERIES ANALYSIS53552355254
Specialization Field Course           
            
1. Year - 2. Term
Ders AdıPy1Py2Py3Py4Py5Py6Py7Py8Py9Py10Py11
SIMULATION TECHNIQUES AND MODELLING45354452435
FUZZY LOGIC53445344453
MULTIVARIATE STATISTICAL METHODS35545554345
DESIGNING AN EXPERIMENT53453355455
LINEAR PROGRAMMING35454535443
SOFT COMPUTING METHODS53454355454
APPLIED STATISTICS IN NATURAL AND SOCIAL SCIENCES45353452455
GENERALISED LINEAR MODELS45354453345
GRAPH THEORY AND APPLICATIONS35553354435
HYPOTHESIS TESTS54353525524
STATISTIC THEORY35243543545
STATISTICAL QUALITY CONTROL54524255354
DECISION-MAKING AND GAME THEORY53454355454
MATHEMATICAL STATISTICS45353452455
OPTIMIZATION54454455454
PANEL DATA ANALYSIS42535425543
POPULATION GENETICS45545344554
SUBSTANTIAL DATA ANALYSIS35243543545
INTEGER PROGRAMMING54535534553
DATA MINING45354245543
VITAL ANALYSIS35435544354
OPERATIONAL RESEARCH44 24533543
Specialization Field Course           
            
2. Year - 1. Term
Ders AdıPy1Py2Py3Py4Py5Py6Py7Py8Py9Py10Py11
Thesis Work            
Specialization Field Course           
            
2. Year - 2. Term
Ders AdıPy1Py2Py3Py4Py5Py6Py7Py8Py9Py10Py11
Specialization Field Course           
            
 

Muğla Sıtkı Koçman Üniversitesi, 48000 Kötekli/Muğla | Tel: + 90 (252) 211-1000 | Fax: + 90 (252) 223-9280
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