Statistics, Data Visualisation, Second Cycle, 5 credits

Learning outcomes

The course's overall aim is to give students
• knowledge of relevant methods for data visualisation adapted to the type of data and the information needs in question
• ability to handle and graphically present the content of large data sets in an effective manner
• ability to take ethical aspects into account in data visualisation.

Content

• Data types
• Importing and manage data, identify and handling missing values
• Introduction to R and ggplot2
• Grammar of Graphics
• Geographical/demographical/spatial data and visualization through maps
• Text data and visualization
• Data ethics

Examinations and grades

Portfolio, 5 credits (Code: A001)
Grades used are Fail (F), Sufficient (E), Satisfactory (D), Good (C), Very Good (B) or Excellent (A).

According to the Higher Education Ordinance, Chapter 6, Section 18, a grade is to be awarded on the completion of a course, unless otherwise prescribed by the university. The university may determine which grading system is to be used. The grade must be determined by a teacher specifically nominated by the university (the examiner).

In accordance with university regulations on grading systems for first and second-cycle courses and study programmes (Vice-Chancellor’s decision ORU 2018/00929), one of the following grades is to be used: fail (U), pass (G) or pass with distinction (VG). For courses included in an international master’s programme (60 or 120 credits) or offered to the university’s incoming exchange students, the A to F grading scale is to be used. The vice-chancellor, or a person appointed by them, may decide on exceptions from this provision for a specific course, if there are special grounds for doing so.

The grades used on this course are Fail (F), Sufficient (E), Satisfactory (D), Good (C), Very Good (B) or Excellent (A).

Comments on grades

The portfolio is built up during the course as the student completes the parts, which form the basis for the grade.
Information about the grading requirements are given at the start of the course.

Modes of assessment

Portfolio, 5 credits (Code: A001)
Continuous examination

For students with a documented disability, the university may approve applications for adapted or other modes of assessment.

For further information, see the university's local examination regulations.

Specific entry requirements

First-cycle courses of 60 credits in statistics, alternatively first-cycle courses of 30 credits in statistics and 60 credits in mathematics, alternatively first-cycle courses of 75 credits in economics, business administration or computer science. The applicant must also have qualifications corresponding to the course "English 6" or "English B" from the Swedish Upper Secondary School.

For further information, see the university's admission regulations.

Other provisions

The course is given in English.

Students who have been admitted to and registered on a course have the right to receive tuition and/or supervision for the duration of the time period specified for the particular course to which they were accepted (see, the university's admission regulations (in Swedish)). After that, the right to receive tuition and/or supervision expires.

Reading list and other learning resources

Required Reading

Chang, W. (latest edition)
R Graphics Cookbook,
E-book
LIBRIS ID:22646034
Available at: https://r-graphics.org

Additional material is provided within the course.