Introduction to Reproducible Analyses in R

21 July 2020 - 13:00-15:00
Emma Rand, N8 CIR

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A workshop to introduce the R programming language and help researchers to make their work transparent and reproducible.


The importance and scale of data in the health sciences means researchers are increasingly required to develop the data skills needed to design reproducible workflows for the collection, organisation, processing, analysis and presentation of data. Developing such data skills requires at least some coding, also known as scripting. This makes your work (everything you do with your raw data) explicitly described, totally transparent and completely reproducible. However, learning to code can be a daunting prospect for many health scientists! That’s where an Introduction to reproducible analyses in R comes in!

R is a free and open source language especially well-suited to data analysis and visualisation and has a relatively inclusive and newbie- friendly community. R caters to users who do not see themselves as programmers, but then allows them to slide gradually into programming.

Who is this course for?

The workshop will by led by Emma Rand of the University of York. It is aimed at health scientists at any career stage interested in experimenting with R to make their analyses and figures more reproducible.


No previous coding experience will be assumed.

Learning outcomes

After this workshop the successful learner will be able to:

  • Find their way around the RStudio windows
  • Create and plot data using the base package and ggplot
  • Explain the rationale for scripting analysis
  • Use the help pages
  • Know how to make additional packages available in an R session
  • Reproducibly import data in a variety of formats
  • Understand what is meant by the working directory, absolute and relative paths and be able to apply these concepts to data import
  • Summarise data in a single group or in multiple groups
  • Recognise tidy data format and carry out some typical data tidying tasks


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