Introduction Workshop to R with application of different statistical methods

Courese dates:
tba

Registration dates:
tba
Typically registration will be opened a few month before course start.

Location:
University of Limpopo

Coordinating university / institution:
University of Bonn, Germany, University of Limpopo, South Africa

Website of the project/course:
tba

Target group:
Master- and PhD-Students. Knowledge of R is not required

Course description  primary learning objectives:
R is a free software environment for statistical computing and graphics. R has been rapidly gaining popularity and is becoming the standard in science across the globe. It offers an almost unlimited range of opportunities from basic descriptive statistics to complex modelling. High-quality plots for publication and even maps can be easily produced using R.

Expected learning outcomes:
Participants will be able to apply the presented methods to their own data.
Participants will get an understanding of R, enabling them to learn and apply new methods on their own.

Learning methods:
Most beginners regard R is as challenging. In this course, we will therefore start at level 0 and overcome the first obstacles! We then proceed to applying statistical analysis (e.g. diversity indices, significance tests, analysis of variance and ordination such as PCA and DCA). We will further produce plots out of the results. The course will be interactive. R-codes will be developed together step-by-step and nobody will be left behind.

Additional Information:
The workshop aims at the application of statistical methods in R rather than introducing or teaching these methods! Participants should therefore familiarize themselves with the above-mentioned methods prior to the course. Participants need to bring their own laptop. The latest versions of R (https://cran.r-project.org/) and R-Studio (https://rstudio.com/products/rstudio/download/) need to be installed prior to the course. Both programs are free for non-commercial use. More information on R: https://www.r-project.org/about.html

Course coordinator:
Kai Behn

Course lead:
Kai Behn