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    (Master's Degree)
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    (Bachelor's Degree)
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    (Associate's Degree)
 
Second Cycle Programmes (Master's Degree)

Graduate School of Health Sciences - Biostatistics and Medical Informatics - Biostatistics - Second Cycle Programme with Thesis



General Description
History
The department of Biostatistics and Medical Informatics has been formed (established) in 2005 under the Medical School of Ege University. The statistical advisory service has started within the department, in 2006 and the Masters program in Biostatistics in 2008 first currently the department has 2 MSc students at thesis and 5 at training.
Qualification Awarded
The students who have successfully completed the program are awarded with the degree of “Master of Science in Biostatistics”.
Level of Qualification
Second Cycle
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 training program is a postgraduate course. The aim of this program is to create graduates who have statistical thinking and are capable to design and analysis of effective experiments in the area of health sciences.
Occupational Profiles of Graduates With Examples
The graduates are expected to find gobs in the research and development sections in public and private sectors.
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
Two examinations are set for each course in the program: one midterm and one final. Homework’s in written and oral form are also given in the courses. The assessment for each course is described in detail in “Individual Course Description”.
Graduation Requirements
Graduation requirements are explained in the section “Qualification Requirements and Regulations” .
Mode of Study (Full-Time, Part-Time, E-Learning )
Full-Time
Address, Programme Director or Equivalent
Ege University, Faculty of Medicine, department of Biostatistics and medical Informatics, Bornova İZMİR Tel: (0232)390 19 85 Fax: (0232)3901996 e-mail: biyoistatistik@ege.edu.tr Head of department: Prof. Dr. Fikret İKİZ ECTS Coordinator: Assoc. Prof. Dr. Mehmet N. ORMAN
Facilities
Two computer laboratories consisting of 70 computers, study rooms with computer which have internet Access and statistical packages

Key Learning Outcomes
1to get the knowledge and the ability of describing and getting information from the data
2to get the knowledge and the ability of analysing the data
3to identify the proper methods of statistical analysis be able to conclude the resuylt of the analysis
4to give statistical advise at the begining stages of preparing health related projects
5to be able write down the final reports of the scientific projects
6to get the knowledge and the ability of using statistical packages

Key Programme Learning Outcomes - NQF for HE in Turkey
TYYÇKey Learning Outcomes
123456
KNOWLEDGE1
2
SKILLS1
2
3
COMPETENCES (Competence to Work Independently and Take Responsibility)1
2
3
COMPETENCES (Learning Competence)1
COMPETENCES (Communication and Social Competence)1
2
3
4
COMPETENCES (Field Specific Competence)1
2
3

Course Structure Diagram with Credits
T : Theoretical P: Practice L : Laboratory
1. Semester
No Course Unit Code Course Unit Title Type of Course T P L ECTS
1 9301195012008 Data Analysis in Medical Research I Compulsory 2 2 0 9
2 930119SEÇ.YL1 ELECTIVE COURSES Elective - - - 21
Total 2 2 0 30
 
2. Semester
No Course Unit Code Course Unit Title Type of Course T P L ECTS
1 9301195022008 Data Analysis in Medical Research II Compulsory 2 2 0 9
2 930119SEÇ.YL2 ELECTIVE COURSES Elective - - - 12
3 BAT102 Fundamentals of Scientific Research Compulsory 2 0 0 3
4 SBEYLSEM500 Seminar Compulsory 0 0 0 6
Total 4 2 0 30
 
3. Semester
No Course Unit Code Course Unit Title Type of Course T P L ECTS
1 SBEYLUAD501 Specialization Field Course Compulsory 0 0 0 4
2 SBEYLTEZ501 Thesis Compulsory 0 0 0 26
Total 0 0 0 30
 
4. Semester
No Course Unit Code Course Unit Title Type of Course T P L ECTS
1 SBEYLUAD502 Specialization Field Course Compulsory 0 0 0 4
2 SBEYLTEZ502 Thesis Compulsory 0 0 0 26
Total 0 0 0 30
 
ELECTIVE COURSES
No Course Unit Code Course Unit Title Type of Course T P L ECTS
1 9301195032010 Sampling Methods Elective 2 0 0 5
2 9301195042010 Mathematical Statistics Elective 2 0 0 5
3 9301195052010 Nonparametric Statistical Methods Elective 2 0 0 5
4 9301195062010 Stochastic Process Elective 2 0 0 5
5 9301195072010 Trial Design and Analysis Elective 2 0 0 5
6 9301195082010 Multivariate Statistical Methods Elective 2 0 0 5
7 9301195092008 Regression Analysis I Elective 3 0 0 6
8 9301195102009 Regression Analysis II Elective 3 0 0 6
9 9301195112010 Clinical Trials Elective 2 0 0 5
10 9301195122010 Applied Catagorical Data Analysis Elective 2 0 0 5
11 9301195132010 Statistical Methods in Health Sciences Elective 2 0 0 5
12 9301195142010 Bioinformatics Elective 2 0 0 5
13 9301195152010 Data Managements Elective 2 0 0 5
14 9301195162010 Genetics Elective 2 0 0 5
15 9301195172010 Quantitative Genetics Elective 2 0 0 5
16 9301195182010 Linear Algebra Elective 2 0 0 5
17 9301195202009 Project Development Elective 1 0 0 5
18 9301195212010 Randomized Controlled Clinical Experiments Elective 2 0 0 5
19 9301195222012 Computer Applied Statistics Elective 3 0 0 6
20 9301195232014 Decision Making in Medicine and Decision Support Systems Elective 2 0 0 5
ELECTIVE COURSES
No Course Unit Code Course Unit Title Type of Course T P L ECTS
1 9301195032010 Sampling Methods Elective 2 0 0 7
2 9301195042010 Mathematical Statistics Elective 2 0 0 7
3 9301195052010 Nonparametric Statistical Methods Elective 2 0 0 7
4 9301195062010 Stochastic Process Elective 2 0 0 7
5 9301195072010 Trial Design and Analysis Elective 2 0 0 7
6 9301195082010 Multivariate Statistical Methods Elective 2 0 0 7
7 9301195092008 Regression Analysis I Elective 3 0 0 7
8 9301195102009 Regression Analysis II Elective 3 0 0 7
9 9301195112010 Clinical Trials Elective 2 0 0 7
10 9301195122010 Applied Catagorical Data Analysis Elective 2 0 0 7
11 9301195132010 Statistical Methods in Health Sciences Elective 2 0 0 7
12 9301195142010 Bioinformatics Elective 2 0 0 7
13 9301195152010 Data Managements Elective 2 0 0 7
14 9301195162010 Genetics Elective 2 0 0 7
15 9301195172010 Quantitative Genetics Elective 2 0 0 7
16 9301195182010 Linear Algebra Elective 2 0 0 7
17 9301195202009 Project Development Elective 1 0 0 7
18 9301195212010 Randomized Controlled Clinical Experiments Elective 2 0 0 7
19 9301195222012 Computer Applied Statistics Elective 3 0 0 7
20 9301195232014 Decision Making in Medicine and Decision Support Systems Elective 2 0 0 7
 
Ege University, Bornova - İzmir / TURKEY • Phone: +90 232 311 10 10 • e-mail: intrec@mail.ege.edu.tr