- Martinez, W &, Martines, A: Exploratory Data Analysis with MATLAB, Chapman & Hall 2005.
- Reiche, N al at, Data-driven storytelling, CRC Press, 2018.
- Peng, Roger D. Exploratory Data Analysis with R, 2015
- Tukey, J W.Exploratory Data analysis, Addison-Wesley 1977
Exploratory Data Analysis, Visualization and Storytelling
Freestanding course
About the course
The course aims to enable the student to critically process the collected data using graphic visualisation and various analytical methods, as well as communicate results from the collected data in an easily understandable way.
Course content
The course contains the following elements:
- organisation of data
- dimensionality reduction
- hidden patterns and clusters
- plotting techniques and mapping for visualisation of distributions, for relationships between variables, visualisation of categorical variables.
- data-based storytelling: influence, technique and ethics.
Syllabus and course literature
You can find a list of literature in the syllabus, along with other details about the course.
Entry requirements and selection
Entry requirements
1. Bachelor of Science in computer science or related subjects.
2. At least 15 credits in programming.
3. At least 7.5 credits in mathematics.
4. Knowledge equivalent to English 6 at Swedish upper secondary level.
Selection
100% University credits completed
Course literature
Course evaluation
The University provides students who are taking or have completed a course with the opportunity to share their experiences of and opinions about the course in the form of a course evaluation that is arranged by the University. The University compiles the course evaluations and notifies the results and any decisions regarding actions brought about by the course evaluations. The results shall be kept available for the students. (HF 1:14).
