Introduction to R (second edition 2024) - FULL

21-22 November & 5-6 December 2024

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

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

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). *Programme* 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 Resea

More information will follow.

University of Geneva, room TBA

This course is coorganised with CUSO StarOmics, CUSO E&E, DSLS-UNIGE.

Travel:PhD students of the CUSO StarOmics/DPEE/MPS are eligible for the reimbursement of incurred travel expenses by train (half-fare card, 2nd class). Claims can be done online via MyCUSO when the activity is over.

Registration fees CUSO DPEE members:
Free Other participants: please contact the programme coordinator at staromics(at)cuso.ch

[CLOSED]

> 2 places available for CUSO StarOmics students

Deadline for registration: TBA

*Cancelation fees: 50 CHF of administrative fees for cancellations after the Deadline of registration.