Ondokuz Mayıs Üniversitesi Bilgi Paketi - Ders Kataloğu
Graduate School of Health Sciences - Biostatistics and Medical Informatics

General Description

History

Aims to start joint postgraduate and PhD programs in the Department of Biostatistics and brings the Institutes of Health Sciences of Ondokuz Mayıs University (OMU) and Hacettepe University (HU) together to ensure the highest academic standards in education and training.

Depends on the provisions of "Regulation on the Joint Postgraduate Education and Training Programs which will be established by the Higher Education Institutions together with other domestic Institutions", which was published by the Board of Higher Education in the Official Gazette dated 22.02.2007 with No. 26442 and on the related provisions of the Law on the Higher Education No.2547, to which the above mentioned regulation refers. Since the Department of Medical Informatics is a separate Department in Hacettepe University, we do not have a special protocol on this issue.

Qualification Awarded

Doctoral Degree of Biostatistics Program

Level of Qualification

Third Cycle

Specific Admission Requirements

LES:50 GRE:650, GMAT:475, Foreign language: B1

Specific Arrangements For Recognition Of Prior Learning (Formal, Non-Formal and Informal)

1. To be eligible for the PhD program in Biostatistics, it is necessary to have a postgraduate degree in either Statistics or Biostatistics.
2. Students who do not have a postgraduate diploma either in Statistics or in Biostatistics cannot apply for the PhD program directly.
3. Students who have postgraduate degree in Statistics have to attend the 1-year Medical Preparatory Class, before starting the PhD program

Qualification Requirements and Regulations

Students who have successfully passed the courses with at least 3.00 academic average are eligible to enter the PhD qualification examination. Depending on the specifications of the scientific field, the PhD qualification examination aims to test whether the student has comprehensive knowledge and skill, ability to synthesize, and also creative power in the major subjects of the scientific field and/or in the subjects related to the study of his/her thesis. Academic evaluation is performed at the end of 4 years (8 semesters) + 2 years (4 semesters). It varies according to the graduate degree. PhD qualification committee can ask a student to take maximum 3 extra courses in cases of failure.

Profile of The Programme

Occupational Profiles of Graduates With Examples

They can work as a statistical analyst, research planner or project coordinator for all research institutions studying on Life Sciences or they can pursue their careers in universities.

Access to Further Studies

Progressing into upper programs realizes via continuing one's career in academic institutions.

Examination Regulations, Assessment and Grading

Student Assessment methods: ° Written and oral examinations. Practical examinations on computer. ° Seminar presentations (Of the terms of the 2 Institutes of Health Sciences, the highest term is applied). If a student wants to raise his/her mark in a course subject, (s)he can attend the course again. The final mark is accepted in the calculation of academic average.

Graduation Requirements

Students admitted to the Ph.D. program with a postgraduate degree have to complete the program with at least 24 credits of course study, and students accepted with a graduate degree with at least 45 credits of course study; according to the European Credit Transfer System, students with a postgraduate degree have to complete the program with at least 120 credits of course study and 120 credits of thesis/art study, and students with a graduate degree with at least 180 credits of course study and 120 credits of thesis study.

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

Address, Programme Director or Equivalent

Programme Director: Yüksel BEK AKTS/DS Coordinator: LEMAN TOMAK BİYOİSTATİSTİK A.D. OMÜ TIP FAKÜLTESİ SAMSUN TEL: 312 19 19 - 2672 MAİL: lemant@omu.edu.tr

Facilities

Programme Outcomes

  1. Alanına yenilik getiren, yeni bir düşünce, yöntem, tasarım ve/veya uygulama geliştiren ya da bilinen bir düşünce, yöntem, uygulamayı farklı bir alana uygulayan özgün bir çalışmayı bağımsız olarak gerçekleştirerek alanındaki ilerlemeye katkıda bulunur.
  2. Alanı ile ilgili en az bir bilimsel makaleyi ulusal ve/veya uluslararası hakemli dergilerde yayınlayarak alanındaki bilginin sınırlarını genişletir.
  3. Alanı ile ilgili ve disiplinler arası sorunların çözümlenmesini gerektiren ortamlarda liderlik yapar.
  4. Yaratıcı ve eleştirel düşünme, sorun çözme ve karar verme gibi üst düzey zihinsel süreçleri kullanarak alanı ile ilgili yeni düşünce ve yöntemler geliştirir.
  5. Kanıta dayalı uygulamaları takip eder ve mesleki uygulamalar ile ilgili kendi alanında kanıt oluşturacak araştırmalar yapar.
  6. Biyoistatistik alanı ile ilgili ileri düzeyde mesleki gelişim ve yaşam boyu öğrenme ilkelerini gerçekleştirdiği çalışmalarda uygular.
  7. Sosyal ilişkileri ve bu ilişkileri yönlendiren normları eleştirel bir bakış açısıyla inceler, geliştirir ve gerektiğinde değiştirmeye yönelik eylemleri yönetir.
  8. Uzman kişiler ile alanındaki konuların tartışılmasında özgün görüşlerini savunur ve alanındaki yetkinliğini gösteren etkili bir iletişim kurar.
  9. Bir yabancı dili en az Avrupa Dil Portföyü C1Genel Düzeyinde kullanarak ileri düzeyde yazılı, sözlü ve görsel iletişim kurar ve tartışır.
  10. Biyoistatistik alanındaki bilimsel, teknolojik, sosyal veya kültürel ilerlemeleri tanıtarak, yaşadığı toplumun bilgi toplumu olma ve bunu sürdürebilme sürecine katkıda bulunur.
  11. Alanı ile ilgili karşılaşılan sorunların çözümünde stratejik karar verme süreçlerini kullanarak işlevsel etkileşim kurar.
  12. Biyoistatistik alanı ile ilgili konularda karşılaşılan toplumsal, bilimsel,kültürel ve etik sorunların çözümüne katkıda bulunur ve bu değerlerin gelişimini destekler.
  13. Diğer sağlık disiplinleri ile çalışabilme deneyimine sahiptir.
  14. Biyoistatistik alanına yönelik yaptığı çalışmalarda doğru istatistiksel yöntemleri seçer ve uygular, doğru yorumlar. Analiz ve sentez yapar.
  15. Biyoistatistik alanı ile ilgili güncel gelişmeleri ve bilgileri çocuk, aile,ulusal değerler ve ülke gerçekleri doğrultusunda toplum yararına kullanır.

Course Structure Diagram with Credits

T:Theoretical,P:Practice, L:Laboratory
Semester 1
Course Unit Code Course Unit Title Type of Course T P L Credit ECTS
SBE-1Optional Subject SDG 0 0 0 0.0 0.0
Total 0 0 0 0.0 0.0
Semester 2
Course Unit Code Course Unit Title Type of Course T P L Credit ECTS
SAUA100Specialization Field Course Zorunlu 4 0 0 0.0 0.0
SBE-2Optional Subject SDG 0 0 0 0.0 0.0
SBESDRSeminar Zorunlu 0 4 0 0.0 0.0
Total 4 4 0 0.0 0.0
Semester 3
Course Unit Code Course Unit Title Type of Course T P L Credit ECTS
SAUA100Specialization Field Course Zorunlu 4 0 0 0.0 0.0
SBETZThesis Zorunlu 4 0 0 0.0 30.0
Total 8 0 0 0.0 30.0
Semester 4
Course Unit Code Course Unit Title Type of Course T P L Credit ECTS
SAUA100Specialization Field Course Zorunlu 4 0 0 0.0 0.0
SBETZThesis Zorunlu 4 0 0 0.0 30.0
Total 8 0 0 0.0 30.0
Semester 5
Course Unit Code Course Unit Title Type of Course T P L Credit ECTS
SAUA100Specialization Field Course Zorunlu 4 0 0 0.0 0.0
SBETZThesis Zorunlu 4 0 0 0.0 30.0
Total 8 0 0 0.0 30.0
Semester 6
Course Unit Code Course Unit Title Type of Course T P L Credit ECTS
SAUA100Specialization Field Course Zorunlu 4 0 0 0.0 0.0
SBETZThesis Zorunlu 4 0 0 0.0 30.0
Total 8 0 0 0.0 30.0
Semester 7
Course Unit Code Course Unit Title Type of Course T P L Credit ECTS
SAUA100Specialization Field Course Zorunlu 4 0 0 0.0 0.0
SBETZThesis Zorunlu 4 0 0 0.0 30.0
Total 8 0 0 0.0 30.0
Semester 8
Course Unit Code Course Unit Title Type of Course T P L Credit ECTS
SAUA100Specialization Field Course Zorunlu 4 0 0 0.0 0.0
SBETZThesis Zorunlu 4 0 0 0.0 30.0
Total 8 0 0 0.0 30.0

Seçmeli Ders Grupları (SDG)

SBE-1 / Optional Subject
Course Unit Code Course Unit Title T P L Credit ECTS
BİS701 Linear Models in Medical Research 3 0 0 3.0 0.0
BİS702 Research in Epidemiology 3 0 0 3.0 6.0
BİS703 Microarrays Data Analysis 3 0 0 3.0 6.0
BİS705 Non-Parametric Regressions 3 0 0 3.0 6.0
BİS706 Advanced Regression Techniques 3 0 0 3.0 0.0
BİS707 Statistics in Genetics 3 0 0 3.0 6.0
BİS708 Design And Analysis Animal Experiments 3 0 0 3.0 6.0
BİS709 Analysis Of Survey in Health Sciencies 3 0 0 3.0 6.0
BİS710 Diagnostic Tests And Roc Analysis 3 0 0 3.0 6.0
BİS711 Logistic Regression And Risk Analysis 3 0 0 3.0 0.0
BİS712 Design And Analysis Of Medical Experiments 3 0 0 3.0 6.0
BİS713 Statistical Quality Control in Analytical Laboratory. 3 0 0 3.0 6.0
BİS714 Analysis Of Repeated Measurements in Medical Research 3 0 0 3.0 6.0
BİS715 Survival Analysis 3 0 0 3.0 6.0
BİS716 Regression Analysis With Applications 3 0 0 3.0 6.0
BİS717 Quantitative Epidemiology 3 0 0 3.0 0.0
BİS718 Analysis Of Drug Experiments 3 0 0 3.0 6.0
BİS719 Residual Analysis in Regression 3 0 0 3.0 6.0
BİS720 Statistical Methods For Reliability And Validity 3 0 0 3.0 6.0
BİS721 Analysis Of Data in Medical Score Forms 3 0 0 3.0 6.0
BİS723 Dose-Response Analysis 3 0 0 3.0 6.0
BİS724 Time Series Analysis 3 0 0 3.0 6.0
BİS725 Structural Equation Models 3 0 0 3.0 6.0
BİS726 R Software Introduction 3 0 0 3.0 6.0
BİS727 Data Mining 2 2 0 3.0 6.0
BİS728 Statistical Methods in Decision-Making Process 3 0 0 3.0 6.0
BİS729 Kategorik Veri Analizi 3 0 0 3.0 0.0
BİS730 Log-Linear Modeller 3 0 0 3.0 0.0
BİS731 Stochastic Processes 3 0 0 3.0 0.0
BİS732 Scientific Research Methods and Ethics 3 0 0 3.0 0.0
BİS733 Örnekleme 3 0 0 3.0 6.0
SBE-2 / Optional Subject
Course Unit Code Course Unit Title T P L Credit ECTS
BİS701 Linear Models in Medical Research 3 0 0 3.0 6.0
BİS702 Research in Epidemiology 3 0 0 3.0 6.0
BİS703 Microarrays Data Analysis 3 0 0 3.0 6.0
BİS705 Non-Parametric Regressions 3 0 0 3.0 6.0
BİS706 Advanced Regression Techniques 3 0 0 3.0 6.0
BİS707 Statistics in Genetics 3 0 0 3.0 6.0
BİS708 Design And Analysis Animal Experiments 3 0 0 3.0 6.0
BİS709 Analysis Of Survey in Health Sciencies 3 0 0 3.0 6.0
BİS710 Diagnostic Tests And Roc Analysis 3 0 0 3.0 6.0
BİS711 Logistic Regression And Risk Analysis 3 0 0 3.0 0.0
BİS712 Design And Analysis Of Medical Experiments 3 0 0 3.0 6.0
BİS713 Statistical Quality Control in Analytical Laboratory. 3 0 0 3.0 6.0
BİS714 Analysis Of Repeated Measurements in Medical Research 3 0 0 3.0 6.0
BİS715 Survival Analysis 3 0 0 3.0 6.0
BİS716 Regression Analysis With Applications 3 0 0 3.0 6.0
BİS717 Quantitative Epidemiology 3 0 0 3.0 6.0
BİS718 Analysis Of Drug Experiments 3 0 0 3.0 6.0
BİS719 Residual Analysis in Regression 3 0 0 3.0 6.0
BİS720 Statistical Methods For Reliability And Validity 3 0 0 3.0 6.0
BİS721 Analysis Of Data in Medical Score Forms 3 0 0 3.0 6.0
BİS723 Dose-Response Analysis 3 0 0 3.0 6.0
BİS724 Time Series Analysis 3 0 0 3.0 6.0
BİS725 Structural Equation Models 3 0 0 3.0 6.0
BİS726 R Software Introduction 3 0 0 3.0 6.0
BİS727 Data Mining 2 2 0 3.0 6.0
BİS728 Statistical Methods in Decision-Making Process 3 0 0 3.0 6.0
BİS729 Kategorik Veri Analizi 3 0 0 3.0 0.0
BİS730 Log-Linear Modeller 3 0 0 3.0 0.0
BİS731 Stochastic Processes 3 0 0 3.0 0.0
BİS732 Scientific Research Methods and Ethics 3 0 0 3.0 0.0
BİS733 Örnekleme 3 0 0 3.0 6.0