Introduction to Data Visualization in R

Length: Four Days
Instructor: Michael Hallquist
Software Demonstrations: R, of course
Lifetime Access: No expirations

Student: $792
Professional: $1032

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Category: Asynchronous, Workshops

Introduction to Data Visualization in R is a four-day workshop focusing on three major topics: 1) theories of graphical design and perception; 2) how to translate these theories to create figures that are informative, clear, and compelling; and 3) using flexible tools in R (especially ggplot2) both for rapid data visualization and creation of publication-quality figures. Relative to other introductory courses on data visualization in R, this workshop emphasizes the principles of graphical perception and teaches you to categorize figures according to a set of graphical idioms that are best suited for different purposes. Throughout the workshop, we will use published figures in the social and behavioral sciences to illustrate both good and bad applications of design and visualization principles. You will also learn how to use the outstanding data visualization tools available in R, culminating in a full walkthrough of a highly communicative figure with custom annotations.

Instructor

Michael N. Hallquist, Ph.D.

Michael Hallquist is an Associate Professor in the Department of Psychology and Neuroscience at the University of North Carolina at Chapel Hill. He is a core faculty member in both the Clinical Psychology program and the L. L. Thurstone Psychometric Laboratory. Read More

Workshop Details

Reviews

So useful and practical in terms of data wrangling and visualization! The content was immensely useful and I learned a lot about not just R but good data storage/wrangling practices, on top of good visualization rules to keep in mind. I loved this class!

Michael's presentations were engaging and interesting. The content helped me think more critically and visually about my own research, which has already benefitted my work.

One of the most helpful parts of this class to me was having Michael walk through R code/syntax as it related to data visualization skills and topics we covered in class.

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