Course info

The course is focused on practical skills in the field of data analysis through their visualization and
effective communication of results to the public. The course is organized in three parts. In the first
part, students will learn to modify data into a form suitable for analysis (e.g. data organization, data
cleaning, data pivoting). In the second part, they will learn the principles and acquire practical
skills of visualizing data distribution (data distribution through histogram, box plot graph, maps)
and relationships between data (e.g. scatter plot, scatter plot matrix, bubble chart, parallel
coordinate plot). All skills will be explained on practical examples in specialized software. In the

Last part, students will learn the principles of graphic presentation and how to avoid the common
mistakes.
1. Preparation of data for visualization. Data formats. Data types.
2. Getting acquainted with the Geoda environment. Exploratory data analysis
3. Entering data into Geoda. Data transformation in Geoda
4. Techniques of data distribution analysis and visualization (histogram, boxplot)
5. Data distribution analysis and visualization techniques (map, cartogram)
6. Consultation of student projects.
7. Analysis and visualization of relationships between data (scatterplot)
8. Analysis and visualization of relationships between data (scatterplot matrix, introduction to
regression)
9. Analysis and visualization of relationships between data (bubble chart, conditional plot, parallel
coordinate plot)
10. Analysis and visualization of time series (averages chart, introduction to diff-in-diff analysis)
11. The most common visualization errors
12. Presentation of student projects
13. Presentation of student projects

Teaching results:

Knowledge - Graduates of the course will learn to modify data into a form suitable for exploratory
data analysis and visualisation. They will learn the basic techniques of graphical data
representation and learn to use the principles of data presentation. At the same time, the most
common errors associated with the visual presentation of data are identified.
Skills - By completing the course, the student will improve analytical and presentation skills
through data visualization.
Competences - Graduates of the course will be able to process data into a suitable for analysis and
identify a suitable visualization technique for convincing presentation of trends, structures or.
extreme values in data. These competencies will serve for better decision-making at the level of
companies as well as in public administration.