NWI-BM083
Data Visualisation for the Life Sciences
Course infoSchedule
Course moduleNWI-BM083
Credits (ECTS)3
Category05 (Specialist)
Language of instructionEnglish
Offered byRadboud University; Faculty of Science; BioWetenschappen;
Lecturer(s)
PreviousNext 1
Lecturer
dr. R.C. Bartfai
Other course modules lecturer
Coordinator
dr. R.C. Bartfai
Other course modules lecturer
Lecturer
dr. K.W. Mulder
Other course modules lecturer
Contactperson for the course
dr. K.W. Mulder
Other course modules lecturer
Coordinator
dr. K.W. Mulder
Other course modules lecturer
Academic year2023
Period
KW2  (06/11/2023 to 28/01/2024)
Starting block
KW2
Course mode
full-time
RemarksMaximum capacity: 60
Registration using OSIRISYes
Course open to students from other facultiesNo
Pre-registrationNo
Waiting listYes
Placement procedureIn order of Study programme
ExplanationIn order of Study programme
Aims
After this course students are able to;
  • make conscious decisions on the trustworthy visualisation of scientific data based on the psychology of figures, applicable on multiple fields of life science. 

Subgoals
After this course students are able to;
  • make conscious decisions on what type of figure best visualises the data, to supports the research objectives.
  • use the psychology of figures to shape the layout and guide readers through figures (to support the research objectives).
  • make conscious decisions on the trustworthy visualisation of scientific data.
Content
One picture is worth a thousand words. A proverb that is gaining relevance in a scientific era and a society where data is increasingly available. Complex and dense information is often visualised in figures to help readers follow the story or convey large amounts of data in one fell swoop. Data visualisation can therefore help gain insights that might otherwise would be missed. These are just a few examples of the use of figures and its therefore no surprise that they are widely used in all types of scientific and mainstream media. However, how data is visualised in figures can sometimes be misleading. In this course you will study the psychology of figures to help you make trustworthy choices when visualising your data in the future.

Instructional Modes:
This course will use the Team Based Learning  (TBL) teaching framework including lectures, at home preparatory assignments and reading material, individual and group Readiness Assurance Tests and collaborative group work.
 
Level

Presumed foreknowledge
No specific prior knowledge is mandatory for this course.
Visualisation using Excel, R (ggplot2) and Python (Seaborn) are supported by the teaching staff to an extent. However, this course focusses on the visualisation of data and not on data analyses, and programming skills are therefore not required.
 
Test information

Team Based Learning components (60%, minimum grade 5.00): 
3x iRAT (Individual Readiness Assurance Test) - 50%
3x tRAT (Team Readiness Assurance Test) - 30%

1x Peer evaluation (Evaluation participation of all team members during the tRAT and application activity.) - 20%
3x Application activity, in which you practice the application of knowledge to be able to complete the end assignment successfully. (not graded for final score)

Final Assignment (40%, minimum grade 5.00):
At the end of the course, you will work on one final assignment in which you will display your knowledge gained during de course.

 
 
Specifics
Maximum capacity: 60.
Everyone will be placed on the waiting list and final enrollment will be decided by the course coordinator and done by the education center. 
Instructional modes
Course
Attendance MandatoryYes

Tests
Team Based Learning Assignment
Test weight3
Test typeProject
OpportunitiesBlock KW2, Block KW3

Assignment
Test weight2
Test typeAssignment
OpportunitiesBlock KW2, Block KW3