732A98 · 6 credits · Advanced level (A1N) · Statistik
Visualization
Active · next start HT 2026
47%
passed the latest regular sitting
DAT3 · 30 Oct 2025 · 17 students
68%
passed the regular sittings, all sittings over the last 5 years
DAT3 · 78 students
Unusually hard in 2025/26
47% passed the ordinary exam in 2025/26 (17 students), against 71% on average in earlier years (61 students).
Part of 1 programme
Other module
DAT3 Examination
- A
- B
- C
- D
- E
- F
Main rounds
68% passed · 78 students
- 47%17
- 56%9
- 79%24
- 77%13
- 73%15
Later rounds
92% passed · 12 students
- 100%7
- 80%5
- Pass a later round: 92% (12 students), compared with 68% (78 students) on the ordinary exam
- Get B or A: 20% (90 students)
Show small sittings (6)
Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
- 50%4
- 0%2
- 67%3
- 50%2
- 100%3
- 0%1
Other modules
Partial exams, hand-ins and labs. They are not part of the figures at the top.
Exam
TENT Examination
- C
- E
- F
No sittings with at least 5 students.
Show small sittings (4)
Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
- 100%1
- 50%2
- 0%1
- 0%1
Hand-in or lab
LAB2 Laboratory work
- P
Main rounds
100% passed · 47 students
- 100%8
- 100%11
- 100%13
- 100%8
- 100%7
Later rounds
100% passed · 5 students
- 100%5
- Pass a later round: 100% (5 students), compared with 100% (47 students) on the ordinary exam
Show small sittings (8)
Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
- 100%2
- 100%2
- 100%3
- 100%4
- 100%1
- 100%2
- 100%1
- 100%3
Hand-in or lab
LAB1 Laboratory workq
- P
No sittings with at least 5 students.
Show small sittings (1)
Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
- 100%1
About the course
Aim
After completion of the course the student should be able to:
- describe major principles for data visualization using static , interactive or dynamic graphs,
- select suitable static, interactive or dynamic visualization techniques for common problems in data visualization,
- produce simple graphs used for analysis and high-quality graphs used for publications,
- use up-to-date open-source and commercial visualization tools to describe the structure of a large and complex data sets, and also discover the hidden patterns and trends in the data,
- show knowledge of visualization methods present in recent research publications.
Content
The course comprises:
- principles of correct data visualization and misleading graphs,
- static tools used for visualizing univariate and bivariate data sets: histograms, bar charts, scatter plots, time series plots,
- visualizing of textual information: word trees and word clouds,
- static tools used for multidimensional data: scatter plot matrices, treemaps, heatmaps, bubble plots, Chernoff faces, star charts, parallel coordinate plots,
- visualization by means of multidimenstional scaling,
- visualizing geographical information by using web applications and standalone software,
- creating animation by combining static graphs,
- animated bubble plots,
- interactive visualization tools: linked graphs, brushing, identification and guided tours,
- producing publication- and presentation-quality graphics from simple graphs.
- Examiner
- Oleg Sysoev
- Main field of study
- Statistik