Advanced data analysis (5523)

  
Coordinating lecturer :Prof. dr. Michelle PLUSQUIN 
  
Co-lecturer :Prof. dr. Tim NAWROT 
  
Member of the teaching team :dr. Brigitte REIMANN 
 dr. Congrong WANG 
 dr. Rossella ALFANO 


Language of instruction : English


Credits: 4,0
  
Period: quarter 2 (4sp)
  
2nd Chance Exam1: Yes
  
Final grade2: Numerical
 
Exam contract: not possible


 
Sequentiality
 
   No sequentiality

Content

In this course the students will get acquainted with systematic reviews, data repositories and handling and processing of large datasets.

The learning goals are as follows:

  • The students can perform a systematic review and make a study flow chart.
  • The students are aware of data repositories and are able to collect data.
  • The students can independently perform basic skills in managing and manipulating data in a reproducible way.
  • The students can independently generate plots such as volcano plots, ideograms, etc. from big datasets.


Organisational and teaching methods
Organisational methods  
Practical  
Project  
Teaching methods  
Demonstration  
Group work  
Report  


Evaluation

Quarter 2 (4,00sp)

Evaluation method
Written evaluation during teaching period80 %
Multiple-choice questions
Take-home assignment
Written exam5 %
Transfer of partial marks within the academic year
Multiple-choice questions, correction for guessing
Oral exam15 %
Transfer of partial marks within the academic year
Open questions
Evaluation conditions (participation and/or pass)
Conditions The evaluation consists of multiple parts. For all parts of the evaluation, at least a score of 8/20 must be obtained in order to pass for the course.
Consequences

A student who achieves a score lower than 8/20 on one (or more) parts of the evaluation will receive a F fail as final result. This final result is not tolerable.

A student who achieves an 8/20 or 9/20 on one (or more) parts of the evaluation will receive 9/20 as the final result, regardless of the weighted average of the scores. This final mark is tolerable.

Eg. 8/20 + 16/20 = 9/20 (tolerable)


Second examination period

Evaluation second examination opportunity different from first examination opprt
No


Learning outcomes
Master of Biomedical Sciences
  •  EC 
  • 12. A graduate of the Master of Biomedical Sciences has an attitude for lifelong learning and for constantly adjusting one's own professional thinking and acting. 

  •  EC 
  • 2. A graduate of the Master of Biomedical Sciences can independently and critically perform a literature search

  •  EC 
  • 4. A graduate of the Master of Biomedical Sciences has knowledge of state-of-the-art techniques within biomedical research and is able to apply these techniques, taking into account the applicable quality standards.

  •  EC 
  • 5. A graduate of the Master of Biomedical Sciences can independently process and statistically analyze research results, and formulate conclusions.

  •  EC 
  • 7. A graduate of the Master of Biomedical Sciences takes a critical attitude towards one's own research and that of others.

 

  EC = learning outcomes      DC = partial outcomes      BC = evaluation criteria  
Offered inTolerance3
1st year Master of Biomedical Sciences - Environmental Health Sciences J
1st year Master of Biomedical Sciences - Molecular Mechanisms in Health and Disease J
first year Master of Biomedical Sciences - Clinical Biomedical Sciences J



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.