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Programming with R

The R programming language has become the standard tool for data analysis, statistics, and bioinformatics. It owes much of this popularity due to its free, open-source, and highly extensible nature. There are tens of thousands of R extensions available, and each adds the ability to perform new types of analyses and operations. This tutorial is intended as a one-day introduction to the language. After the workshop, students will be able to write R code using RStudio, analyze and manipulate data in R, create publication-quality graphics, parallelize and performance-optimize their scripts, and run analyses both on their own computer and clusters operated by organizations like CAC, SciNet, and SHARCNET.

Instructor: Jeff Stafford - Centre for Advanced Computing, Queen's University

Prerequisites: No programming experience required

Required Software:

R -

RStudio Release Preview -