De elektronische studiegids voor het academiejaar 2026 - 2027 is onder voorbehoud.





Pragmatic Trial Design in Global Health Research (3772)
Coordinating lecturer:Prof. dr. Niel HENS 
Co-lecturer:dr. Tarylee REDDY 
Member of the teaching team:dr. Jade MEMBREBE 
 dr. Leyla KODALCI 

Credits: 3,0
Study load hours: 81
Period: semester 1 (3sp)

Language of instruction: English
Exam contract: not possible

2nd Chance Exam1: Yes
Final grade2: Numerical
Tolerance3: See included in these programmes
Sequentiality
No sequentiality


Prerequisites

Corequisite for this course is basic knowledge of fundamental statistical concepts. Although no specific pre-requisites, this course will cover advanced statistical topics.


Content

Selected topics in computational biology are covered in this course each academic year. 

This course is organized in cooperation with lecturers from our South partner.


Compulsory course material
 

Handouts made available by the instructors on Blackboard.


Organisational and teaching methods
Organisational methods  
Lecture ✔  
Project ✔  


Evaluation

Semester 1 (3,00sp)

Evaluation method
Written evaluation during teaching period75 %
Transfer of partial marks within the academic yearYes, no resit exam
Homework✔
Paper✔
Oral exam25 %
Open questions✔
Additional information

No participation at all in the assignments/projects will imply exclusion of participation in the final exam and incomplete participation will result in a reduced score of the final score.

Second examination period

Evaluation second examination opportunity different from first examination opprt
No


Learning outcomes
  EC = learning outcomes      DC = partial outcomes      BC = evaluation criteria  
Master of Statistics and Data Science
  •  EC 

    • The student can handle scientific quantitative research questions, independently, effectively, creatively, and correctly using state-of-the-art design and analysis methodology and software.

     
  •  DC 

    • ... correctly using state-of-the-art analysis methodology.

     
  •  DC 

    • ... correctly using state-of-the-art software.

  •  EC 

    • The student can work in a multidisciplinary, intercultural, and international team.

  •  EC 

    • The student has the habit to assess data quality and integrity. 

  •  EC 

    • The student is capable of acquiring new knowledge.

  •  EC 

    • The student knows the societal relevance of statistics and data science.

 
Included in these programmesTolerance3
2nd year Master Bioinformatics Y
2nd year Master Bioinformatics - icp Y
2nd year Master Biostatistics Y
2nd year Master Biostatistics - icp Y
2nd year Master Quantitative Epidemiology Y
2nd year Master Quantitative Epidemiology - icp Y
Exchange Programme Statistics Y



1   Education, Examination and Legal Position Regulations art.12.2, section 2.
2   Education, Examination and Legal Position Regulations art.15.1, section 3.
3   Education, Examination and Legal Position Regulations art.16.9, section 2.