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Research Software Learning Online: R and RStudio

Accessing R and RStudio

R Studio imageR 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 UniApps and 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: https://www.r-project.org. There is an open-source version of RStudio available from the RStudio website: https://rstudio.com/products/rstudio/download/.  There are instructions on installing R and RStudio onto your own device here: https://datacarpentry.org/r-socialsci/setup.html

 

Image: CC BY-SA: https://commons.wikimedia.org/wiki/File:KnitR_in_RStudio.png

Please note that O'Reilly deletes content in December and June. If you are linking to courses on this platform we advise that you check that they are still running in January and July of each year. 

Searching for more courses on R

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

If you cannot see 'Learning Path' and 'Video' as an option under the Format filter you should delete the site cookies and refresh the page. 

Getting started courses

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. 


Learn R Programming (1.5 hours)

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 StudioLearn R Programming
  • Working with variables and functions
  • Working with different data formats (vectors, matrices, data frames)
  • Reading data into R and some summary statistics

R Programming Fundamentals (2.5 hours)

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 RStudioR programming fundamentals
  • Variable types
  • Data import and export
  • Data visualisation
  • Data management 

R Programming LiveLessons: Fundamentals to Advanced (10.5 hours)

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 RR programming live lessons
  • 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

Intermediate and advanced courses

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. 


R Programming (21 hours)

This is the ultimate go-to video resource for new users of R but not an introductory course for complete beginners. This course is for those with a basic knowledge of R who want to focus on specific tasks. The course covers: 

  • Getting started, data structures and basic functions in RR Programming
  • Reading different data formats into R
  • Making statistical graphs
  • Basics of programming 
  • Coding for data manipulation / wrangling
  • Creating reports and slideshows 
  • Introduction to Shiny
  • Building packages 
  • Statistics: linear models, splines, GAMs, decision trees, time series, Bayesian modelling, machine learning and network analysis 

R Programming for Statistics and Data Science (6.5 hours)

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 RStudioR programming for statistics and data science
  • 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