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Principles of Data Visualization

The communicative power of eloquent data visualization
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Course description

Requirements:

  • None

Course overview:

Effective visualization of data plays a key role in scientific research. Good graphics can make research memorable and credible. In this seminar, we will discuss the importance of data visualizations and key considerations for their construction and interpretation.

Please note that this is not a programming course, but a seminar on principles of visualizations.

Please consider this seminar was part of the “Data Visualization Workshop” in 2022 & 2023.


Topics:

Data visualization allows us to represent and understand information in a fast and intuitive manner. What makes great charts great? And what makes bad charts bad, or even sometimes misleading? It is easy to view charts as factual and impartial, but every chart tells a story and highlights different aspects of the underlying data. Through a series of real-life examples, we will discuss the importance of clear and deliberate data visualization, which ingredients we need to combine to create clear and precise visualizations and learn how communicate as clearly through our charts as in our writing.

If you would like to learn how to code more advanced graphics in R, please check out our course Graphics with R. If you would like to learn which plots to use for what kind of data, we recommend our course Introduction to Statistics or our advanced statistics courses.


Methods:

  • The seminar is intended to give an overview on different aspects of data visualization.

Format:

  • Duration: 3.5 hours
  • Language: English
  • This course will be offered either on campus (in person), or online.
  • For online courses we use the software Zoom.

 

Dates and Application:

  • Workshops provided for Helmholtz Munich:
    • In 2024 the workshops will be offered two times in cooperation with the graduate school HELENA.
    • You can check the current dates and whether the courses are already fully booked here*.
    • Please read the corresponding FAQ* before applying via the forms of CaMS*.

 * Links marked with * are only available for Helmholtz Munich staff.