What is R?
R is an open-source, widely used statistical programming language, that is easy to learn and, thanks to its many extensions, can be used as a general-purpose programming language. R was first released in 1993 and has since risen greatly in popularity, being used in academic institutions as well as companies such as the BBC, NHS, Google, Facebook, Twitter, Microsoft, Wellcome, Sanger Institute, New York Times and Mozilla.
R is simple to use and easy to read, this makes sharing your code easier and enables you to write your code faster. This is taken further by the Tidyverse ecosystem within R, that provides even easier to read code as well as excellent documentation. R is one of the best choices for data science and machine learning due to its wide pool of libraries for statistics, data manipulation and wrangling, data visualisation, and modelling; it is used across many sectors such as finance, healthcare, technology and retail for these purposes. R is the gold standard choice for data visualisation in data science thanks to the ggplot2 library and its many extensions. R also has one of the best open-source Integrated Development Environments (IDE) available in RStudio, not only does it make programming in R easy, it makes it simple to create documents with your code and outputs in various output formats such as HTML, Word, Powerpoint, and PDF.
The R workshops are designed to give you good working knowledge of primary tools, concepts, and skills that form the foundation of statistical programming projects in R, and give you the essential tools you will need to use R for analytical and quantitative work, from cleaning your data to visualising and analysing.
No prior experience is required and it is also suitable for those looking for a refresher.
Each workshop is in person and two hours long. You will work with fellow learners, utilising your prior experience, web searches, and in-application Help features to find the solutions to real-world problems, with an R expert on hand if you get stuck.
Click here to book your place.
Once you are booked on the course, you will be able to choose which skill set you work on from the list below.
Location
This workshop takes place in LBR.R.08 located on the lower ground floor of the library. Computers are provided.
Technical Requirements
All software is provided on lab computers. If you would like to use your own laptop you will need install the following software:
R ( Mac / Windows)
RStudio Desktop (Mac/Windows - you must install R first to use RStudio)
XQuartz (install if using Mac with operating system greater than 10.5)
- Worksheet 1: First steps with R
This worksheet is for those who have not used R previously or are wanting a refresher. We will explore some of the key concepts you’ll need to use R through a project looking at health metrics.
- Worksheet 2: Data Cleaning
In this worksheet, we will be preparing a dataset for analysis, handling common data cleaning tasks you will come across in R. We will also be performing some transformations and aggregations of a dataset. Keep in mind that when it comes to analysis, data cleaning is what takes up most of your time!
- Worksheet 3: Data visualisation
In this worksheet, we will be exploring a dataset in preparation for analysis through data visualisation. Reviewing your data is a crucial step before starting an analysis. We will go through several visualisations and how to get useful summary statistics on your data.
- Worksheet 4: Data analysis
In this worksheet, we will be analysing a dataset using several common statistical tools including t-tests, ANOVAs, and regression. You will also be given the option to explore different datasets which have been provided.