Introduction to R

23-24 June & 30 June-1 July 2025

José Manuel Nunes, Dr., UNIGE
Nicolas Hulo, Dr., UNIGE

José Manuel Nunes, Dr., UNIGE
4 assistants

The R environment for statistical computing and graphics has become an undisputed reference for data analyses in Biology and many other sciences. It combines unparalleled facilities to learn, design, explore, analyse, graph, tabulate, draft and report computational/statistical data analyses. Its simple and reliable yet powerful extensions' system (packages) makes R the environment where many new methods are developed. The RStudio interface provides an easy to use interface to this very complete system that runs almost equally in a large number of operating systems. Furthermore, R is free software. The course includes some topics in statistics and presents some programming related features of R but it is not intended as a introductory or refresher statistics course or an introduction to programming.

Learning objectives: By the end of the course, the participants are expected to: be able to make basic exploratory data analyses write R expressions to perform everyday tasks in data analysis produce tables and graphics and make them available as files be capable of reading, understanding and writing basic R scripts use the help facilities available Previous knowledge/skills.

The course assumes no prior knowledge of the R system nor any specific background except being familiar with basic text editing and file manipulation (copy, move) in computer systems. Technical requirements: You may use the computers provided by the University or bring your own laptop in which case you'll need to make a 10 minutes check-up test two days prior to the course (details provided upon confirmation).

Program: R System Overview; Data Types (vectors, data frames, lists); Subset Selection - Importing and Exporting Data from/into Files (read/write); Numerical Summaries - Using Functions Effectively; Graphical Summaries; Classical Statistical; Tests; Families (tests, probability distributions, functions); The (self) Help System & Scripting for Reproducible Research.

More Information will follow

University of Geneva, Room TBA

This course is organized in collaboration with the CUSO Doctoral Programs in Ecology & Evolution, Microbial Sciences and StarOmics and the Doctoral School in Life Sciences of Neuchâtel (DSLS)

Reimbursements for CUSO MPS Students:
Train ticket, 2°class, half-fare from your institution to the place of the activity 

Reimbursement of your travel tickets can be asked online through your MyCUSO. 
See HERE for the procedure.

For any question concerning reimbursement please contact the CUSO MPS coordinator Debora Zoia

REGISTRATION IS CLOSE

Deadline for registration: TBA

4 places available for CUSO MPS Students

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