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Michael Schulte-Mecklenbeck

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University of Ljubljana, University of St.Gallen
University of Berne

Course location

University of Ljubljana, University of St.Gallen

Home university

University of Berne
Schulte-Mecklenbeck
Michael Schulte-Mecklenbeck earned a Phd in Psychology at the University of Fribourg, Switzerland and completed his Habilitation in Business Administration at the University of Bern, Switzerland. He held positions at the Columbia Business School, New York; the Max Planck Institute for Human Development, Berlin and the Nestlé Research Center, Lausanne. Currently he is holding the position of an Associate Professor for methodology and decision science at the University of Bern. His research interests are focused on processes of information acquisition and the connected measurement methods (eye-tracking, mousetracking). He edited two books on this topic which were both widely recognized as the standard references for process tracing methods. Professor Schulte-Mecklenbeck is a proponent of open science, open publishing and open data and is the node leader in the Swiss Replication Network for the University of Bern.

Courses taught by this instructor

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B = Basic
M = Intermediate
A = Advanced

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Course

Description

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B = Basic
M = Intermediate
A = Advanced

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Communicating and Visualizing Data with R

Learning objectives The creation and communication of data visualizations is a critical step in any data analytic project. Modern open-source software packages offer ever more powerful data visualizations tools. When applied with psychological and design principles in mind, users competent in these tools can produce data visualizations that easily tell more than a thousand words. In this course, participants learn how to employ state-of-the-art data visualization tools within the programming language R to create stunning, publication-ready data visualizations that communicate critical insights about data. Prior to, during, and after the course participants work their own data visualization project. Course content Each day will contain a series of short lectures and demonstrations that introduce and discuss new topics. The bulk of each day will be dedicated to hands-on, step-by-step exercises to help participants ‘learn by doing’. In these exercises, participants will learn how to read-in and prepare data, how to create various types of static and interactive data visualizations, how to tweak them to exactly fit one’s needs, and how to embed them in digital reports. Accompanying the course, each participant will work on his or her own data visualization project turning an initial visualization sketch into a one-page academic paper featuring a polished, well-designed figure. To advance these projects, participants will be able to draw on support from the instructors in the afternoons of course days two to four.
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B

2023

2023

Communicating and Visualizing Data with R

Learning objectives The creation and communication of data visualizations is a critical step in any data analytic project. Modern open-source software packages offer ever more powerful data visualizations tools. When applied with psychological and design principles in mind, users competent in these tools can produce data visualizations that easily tell more than a thousand words. In this course, participants learn how to employ state-of-the-art data visualization tools within the programming language R to create stunning, publication-ready data visualizations that communicate critical insights about data. Prior to, during, and after the course participants work their own data visualization project. Course content Each day will contain a series of short lectures and demonstrations that introduce and discuss new topics. The bulk of each day will be dedicated to hands-on, step-by-step exercises to help participants ‘learn by doing’. In these exercises, participants will learn how to read-in and prepare data, how to create various types of static and interactive data visualizations, how to tweak them to exactly fit one’s needs, and how to embed them in digital reports. Accompanying the course, each participant will work on his or her own data visualization project turning an initial visualization sketch into a one-page academic paper featuring a polished, well-designed figure. To advance these projects, participants will be able to draw on support from the instructors in the afternoons of course days two to four.
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