Using R

09:00 - 11:20 BST |  Monday 12th April 2021

Faculty

Workshop organiser: Professor Rik Henson, Cambridge University UK

• Simon White, MRC Biostatistics Unit, UK - R introduction (philosophy, syntax, data structures, etc)
• Athanasia Mowinckel, University of Oslo Norway - R for visualisation (plots, graphics, etc)
• Delia Fuhrmann, Kings College London UK - R for basic stats (t-tests, anovas, general linear model, linear mixed effects models, etc)
• Rogier Kievit, Donders Instittue at Radboud University, The Netherlands - R for multivariate stats (factor analysis, structural equation modelling, etc)
• Rik Henson, MRC Cognition and Brain Sciences Unit UK - R for Bayesian analysis (brief introduction to Bayes factors, sequential designs)

Description and aims of workshop

A practical session to set you up for using R programming language in your science life! 

One of the R's great strengths is that it is open source, and is not severely restricted to operating systems - it compiles and runs on a wide variety of UNIX platforms and similar systems (including FreeBSD and Linux), Windows and MacOS. 

Being open source, R is covered under the GNU General Public License Agreement, highly cost effective for a project of any size,  developments in R happen at a rapid scale, and the community of developers is huge.

R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, …) and graphical techniques, and is highly extensible. It produces well-designed publication-quality plots with ease, including mathematical symbols and formulae where needed. 

Find out why R is so popular in academia, so important for Open Science, and how you can use it yourself.

Recommended reading! - If you want to get ahead and start exploring R beforehand, and/or continue reading afterwards, see this excellent R for Data Science website.

 R logo from The R Foundation, used via CC-BY-SA 4.0.