R is an open-source programming language that is used for programming, data analysis and data visualisation. It is widely used for statistical analysis. RStudio is a Graphical User Interface (GUI) for R.

R and RStudio are available on all of the University-managed computers across campus and via UniDesk. Staff and students can install R and RStudio onto their University devices via the Software Centre. R is open-source software that you can download for free from the R Project website. There is an open-source version of RStudio available from the RStudio website. There are instructions on installing R and RStudio onto your own device via the Data Carpentry website.

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- Work remotely with UniApps and UniDeskUniApps and UniDesk enables students and academic staff to access software, a University style desktop and print to campus remotely from their own device.

You can search for more courses and resources for learning R on O'Reilly Learning. Enter 'R' into the search bar on the home page. We recommend that you filter the results:

- use the 'Format' filter to filter by resource type: courses are listed as 'Learning Path' or 'Video'
- use the 'Topic' filter to filter for courses specifically on R

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These courses are suitable for researchers who are completely new to using R and RStudio.Getting started courses that require you to install R and RStudio will go through the steps to install the relevant programme. If you are using a University-managed PC please see the access information at the top of this page.

This is a good introductory video course on R which will take you through setting up R and RStudio, the different data types and formats and some basic commands for data manipulation and summarising data. A good start to learning R from which you can engage with the longer, more in-depth courses. This course covers:

- Getting started with R and R Studio
- Working with variables and functions
- Working with different data formats (vectors, matrices, data frames)
- Reading data into R and some summary statistics

This is a good introductory video course for those who are new to R and new to coding. It covers the basics of R, introduces data visualisation and data management. Once you have completed this course you should feel more confident to take some of the more in-depth courses. The course covers:

- Getting started with R and RStudio
- Variable types
- Data import and export
- Data visualisation
- Data management

This video course is suitable for those who are new to R but perhaps not new to using a code-based statistical analysis programme. The course starts with the basics of using R and then progresses to more advanced topics. The course covers:

- Getting started with R
- The basic building blocks - data types
- Advanced data structures in R
- Reading data into R
- Making statistical graphs
- Basics of programming
- Data wrangling - data manipulation
- Manipulating strings
- Basic statistics
- Linear models - linear, logistic and Poisson regression, survival data
- Other models - splines, GAMs, decision trees
- Time series analyses
- Clustering
- Creating reports and slideshows with package knitr
- Package building

For those of you who are already familiar with R there are a wide range of courses that you can used to expand your knowledge and skills. Many of these can be dipped in- and out- of as needed. We have provided a selection of curated courses for you and you can search for other courses on O'Reilly Learning.

This 15-hour video teaches you how to program in R even if you are unfamiliar with statistical techniques. It starts with the basics of using R and progresses into data manipulation and model building. Users learn through hands-on practice with the code and techniques. New material covers chaining commands, faster data manipulation, new ways to read rectangular data into R, testing code, and the hot package Shiny.

Based on a course on R and Big Data taught by the author at Columbia

- Designed from the ground up to help viewers quickly overcome R’s learning curve
- Packed with hands-on practice opportunities and realistic, downloadable code examples
- Presented by an author with unsurpassed experience teaching statistical programming and modeling to novices
- For every potential R user: programmers, data scientists, DBAs, marketers, quants, scientists, policymakers, and many others

This is quite an in-depth video course that, for more experienced users of R, would be useful ‘how-to’ learning resource. The course covers:

- Getting started with R and RStudio
- Vectors and vector operations
- Matrices and data frames
- Fundamentals of programming in R
- Manipulating and visualising data
- Statistics: descriptive statistics, hypothesis testing and linear regression