Data visualization

Faculteit Gedrags- en MaatschappijWetenschappen
Jaar 2019/20
Vakcode SOMINDW09
Vaknaam Data visualization
Niveau(s) universitaire minor
Voertaal Engels
Periode semester I b
ECTS 2.5
Rooster 4 (interactive lectures + practicals)

Uitgebreide vaknaam Data visualization
Leerdoelen At the end of the course, the student is able to:
1. Understand why visualization is such an important part of the scientific process when it involves data;
2. Interpret common types of visualization and know the advantages and limitations of these;
3. Understand why different types of data require different types of visualization;
4. Understand and evaluate a dataset and its variables;
5. Create (beautiful!) visualizations via the programming language R;
6. Apply programming skills to transform data into forms suitable for visualization;
7. Communicate findings that arise from your data.
Omschrijving In this course, you’ll learn how to effectively and beautifully visualize your data and communicate your results. Through lectures and practicals you learn about common types of visualization, their pros and cons, and how to create them yourself. The course starts with visualizing single variables and end with more complex visualizations like networks and maps. You’ll also learn how to work with datasets and transform your data in such a way that you’ll be able to make any visualization you’d like. You’ll learn that visualizations are an ideal way to assess data quality. While making these visualizations, you’ll be gently exposed to programming, and already after the first lecture you will be able to program your first graphs. At the end of the course, you will be able to make much better visualizations than is common in science currently.
Uren per week 4
Onderwijsvorm werkcollege
(Lectures + practicals)
Toetsvorm opdrachten
(Weekly assignments (pass/fail) + graded final visualization project)
Vaksoort bachelor
Coördinator dr. G. Stulp, PhD.
Docent(en) dr. G. Stulp, PhD.
Verplichte literatuur
Titel Auteur ISBN Prijs
https://r4ds.had.co.nz/
https://serialmentor.com/dataviz/
https://socviz.co/

Entreevoorwaarden
Opmerkingen
Opgenomen in
Opleiding Jaar Periode Type
Minor Data Wise: data science in society 3 semester I b keuze