Visualization, 6 credits

Main field of study

Course level

Advancement level

Course offered for

• Master´s Programme in Statistics and Data Mining

Entry requirements

A bachelor’s degree  in one of the following subjects: statistics, mathematics, applied mathematics, computer science, engineering, or equivalent. Completed courses in calculus, linear algebra, statistics and programming are required. 
Documented knowledge of English equivalent to Engelska B/Engelska 6.

Intended learning outcomes

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.

Course 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.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                      

Teaching and working methods

The teaching comprises lectures, seminars, and computer exercises complemented by self-studies. Lectures are devoted to presentations of theories, concepts and methods. Computer exercises provide practical experience of data visualization. The seminars comprise student presentations, discussions of the computer assignments and presentation of research papers related to visualization.
Language of instruction: English.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                      

Examination

Written reports on computer exercises. Active participation in the seminars. Presentation of a research article. One final written or oral examination. Detailed information about the examination can be found in the course’s study guide.

Students failing an exam covering either the entire course or part of the course two times are entitled to have a new examiner appointed for the reexamination.

Students who have passed an examination may not retake it in order to improve their grades.

Grades

Other information

Planning and implementation of a course must take its starting point in the wording of the syllabus. The course evaluation included in each course must therefore take up the question how well the course agrees with the syllabus. 

The course is carried out in such a way that both men´s and women´s experience and knowledge is made visible and developed.

Department