R Made Easy

Last Thursday I gave an informal introduction to R at the Institute of Botany in Innsbruck. Despite R’s non-user-friendly reputation, the R Made Easy lecture attracted 25 people: Master students, PhD students post-docs, and a few regular employees. During four hours, the basic functionalities of R, and the most recent data handling and visualisation methods (ie, tidyverse) were covered.

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Giving lectures

I’m intensively preparing the next course I will give to Master students. It requires a lot of documentation, yet a synthetical mind. Finding a logical line in various topics, to keep the student’s attention, is also a challenge. But giving lectures is a great feeling, and sharing with students this knowledge I got when I was at their place before is thrilling to me.

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Introduction Course to R

I gave today a relaxed “hands-on” course to R, to introduce some colleagues to the syntax of this reference software for statistical analyses and production of peer-reviewed-journals quality graphs. After a brief explanation of what R is, I explained the major elements of the R language, and guided my colleagues to produce a live linear model and graph on a simple dataset. Then they replicated by their own the procedure on another dataset (according to the scientific method), and presented the results and conclusion to the audience.

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