Microcredential ekomex: Learning Data Visualisation in R
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This 2-day short course teaches practical skills for making data-driven graphs using the ggplot2 package in R.
What Is This Course About?
This comprehensive, introductory course equips you with the knowledge and skills to interpret and present your data visually. It will help you understand and showcase trends in your data using the powerful ggplot2 package in R, enabling you to select the most fitting visual representations. By the end of the course, you will have the proficiency to translate complex data into clear, meaningful visuals that effectively communicate your data's story.
Learning Goals
- Understand the ggplot2 syntax and principles: Gain a firm understanding of the ggplot2 package, its syntax, and the underlying grammar of graphics principles it is built upon.
- Create a variety of plot types: Learn how to create and customize different types of plots, including scatter plots, bar plots, line plots, histograms, and more, using ggplot2.
- Enhance plot aesthetics: Understand how to manipulate elements like color, size, shape, and theme to make visually pleasing and effective plots that best represent the data.
- Implement data transformations and statistical summarization: Learn how to use ggplot2 to transform data, summarize it statistically, and display those summaries on your plots.
- Build multi-layered plots: Develop the ability to build complex, multi-layered plots by adding multiple geometries to the same plot, which will allow you to visualize multiple dimensions and aspects of your data in a single graph.
Assignments for the Course
Take-home exercises, group exercises.
Schedule
- 10:00-12:00h
- 13:00-15:00h
Recommended Readings for the Course
- Wickham, H. (2011). ggplot2. Wiley interdisciplinary reviews: computational statistics, 3(2), 180-185.
- Wickham, H. (2016). Programming with ggplot2. ggplot2: Elegant graphics for data analysis, 241-253.
Who is Your Instructor?
Dr. Massimiliano Canzi is a Data Scientist and Lab Manager at the University of Konstanz's Linguistics Department. He utilizes R programming for linguistic and cognitive science experiments and teaches statistics to Linguistics Master's students. His research involves quantitative and experimental methodologies and tools such as electroencephalography and pupillometry.
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