Difference between revisions of "Training:SummerSchool2016:Programme:R"
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= Programming with R = | = 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 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. This workshop is aimed at users with little to no prior experience with R and is a great way to learn a new programming language! |
'''Instructor:''' Jeff Stafford - Centre for Advanced Computing, Queen's University | '''Instructor:''' Jeff Stafford - Centre for Advanced Computing, Queen's University | ||
Revision as of 21:05, 28 June 2016
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. This workshop is aimed at users with little to no prior experience with R and is a great way to learn a new programming language!
Instructor: Jeff Stafford - Centre for Advanced Computing, Queen's University
Prerequisites: No programming experience required
Required Software:
R - https://www.r-project.org/
RStudio Release Preview - https://www.rstudio.com/products/rstudio/download/preview/
