Introduction to R

March 9-10 & 23-24, 2023

José Manuel NUNES

Dr Jose Manuel Nunes, 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).

• 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

University of Geneva

When?
March 9-10 & 23-24
10:10 - 17:00

Where?
University of Geneva - Quai Ansermet 26, 1205 Geneva - Pavillon Ansermet, room 119

Questions?
Catherine Suarez
@: [email protected]

Note: This course is coorganised with CUSO StarOmics, CUSO MPS, CUSO Microbiology and UNINE-DPOB

Deadline for registration: 17.02.2023 --> extended to 24.02.3034

CUSO members: FREE.

Cancellation Policy
In case of cancellations, before the first deadline (17.02.2023): free
Late cancellations (after 17.02.2023) or no-show: 50 CHF administrative fee

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