NHS-R Introduction to R and R Studio > Event Information

Event Information

Course content and pre-requisites

Who should attend / target audience

Data Analysts and anyone interested in learning about R.

The course is informal and is intended to help you feel comfortable with asking questions in the workshop and beyond the course through the NHS-R Community.

Pre-requisites:

No prior knowledge of R is required; however, it is assumed that you will have a moderate level of computer literacy. For example, you will be able to navigate to drives and files and be confident in searching for solutions to technical problems on the internet. You will work with, or have an interest in, data.

You are expected to have completed the prework to set up either a laptop with R, RStudio, some packages and download data or have access to and set up an account with RStudio Connect. The RStudio Connect workspace has everything pre-loaded but still requires accessing through an account (some organisations may block this site too so please do check it in advance).

What delegates will gain/ learning outcomes

Why R:

R is one of the most powerful data science software solutions used the world over and is being actively promoted by the NHS-R Community. Analysts throughout the NHS and in Social Care are discovering the huge potentials of R which range from analytical and statistical work to creating websites and interactive reports. It’s a hugely flexible and versatile language that has far extended its original use for statistics.

Learning Outcomes:

After this one-day introduction, delegates will:

  1. See examples of R in producing healthcare related visualisations and use publicly available healthcare data to answer questions.
  2. Recognise and understand key terms often used by users of R.

Furthermore, delegates will be able to:

  1. Interact with R using the RStudio environment.
  2. Learn how to set up some of the accessibility features of RStudio.
  3. Take charge of their workflow using RStudio projects.
  4. Import data into R using csv files (other data sources will be discussed).
  5. Carry out data manipulation using simple steps to solve complex problems.
  6. Join multiple tables together.
  7. Produce and save plots using ggplot2.
  8. Learn how to find more information on functions within R packages.
  9. Open an RMarkdown template and learn how to get started in producing an integrated text and code report.
  10. Take away ideas for continuing learning after the course.

Programme Outline (including objectives)

Timings in the course vary depending on any issues that people may encounter. It will be a recorded session so you will have an opportunity to catch up or go over information again at a later date.

  • Introduction to R and RStudio Some examples of the use of R and how to set up R Studio
  • Using Projects How and why to use projects in R Studio
  • Importing data How to use the import wizard in R Studio and try importing example Excel spreadsheets
    Break
  • Introduction to ggplot2
    An introduction to ggplot2 and plotting data
    Lunch
  • What does this function do?
    How to locate help functions
  • Data wrangling with dplyr
    Introducing a few of the key dplyr functions to help shape and tidy data
  • Naming objects
    How to create an object from some code or a plot
    Break
  • Relational data
    How to join data using dplyr
  • RMarkdown
    Introducing RMarkdown reports
  • Ongoing Learning
    Suggestions for further R resources