Data visualization

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 reactive graphs and dashboards. 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	2
Onderwijsvorm	werkcollege (Lectures + practicals)
Toetsvorm	opdrachten (5 weekly assignments (2 pass/fail + 3 graded))
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	Although visualizations will be created through R, no programming experience is required.
Opmerkingen
Opgenomen in	Opleiding Jaar Periode Type Minor Data Wise: data science in society 3 semester I a keuze