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  • Description: R is a highly-regarded, free, software environment for statistical analysis that is used in a wide variety of academic and industrial sectors. Furthermore, it has many useful features that promote and facilitate reproducible research. In this course, we give an introduction to the R environment and explain how it can be used to import, manipulate and analyse tabular data. After the course you should feel confident to start exploring your own dataset using the materials and references provided.

Please note that although we will demonstrate how to perform statistical analysis in R, we will not cover the theory of statistical analysis in this course. Those seeking an in-depth explanation of how to perform and interpret statistical tests are advised to see the list of related courses. Moreover, those some programming experience in other languages (e.g. Python, Perl) might wish to see the follow-on "Data Analysis and Visualisation in R" course

  • Format: Presentations, demonstrations and practicals

  • Frequency: A number of times per year

  • Prerequisites:

    No prior programming experience is required, but those attending should be able to use a plain text editor. A very basic knowledge of UNIX would be an advantage, but nothing will be assumed and extremely little will be required.

  • Aims: During this course you will learn about:

    • The RStudio interface to R
    • The many ways to access help about R
    • Basic object types in R
    • Importing tabular data into R
    • Manipulating data in R
    • Using in-built functions
    • Statistical testing in R
    • Executing basic data analysis workflows in R
    • Basic Plotting
    • Customizing plots
    • Basic programming with if/else statements and for loops
    • Creating reproducible reports in R

  • Objectives: After this course you should be able to:

    • Import data and plot graphs
    • Perform statistical tests in R
    • Create a documented and reproducible piece of R code
    • Know how to develop your skills in R after the course
    • Install and start to use Bioconductor packages

  • Related courses:-

    • Introduction to Statistical Analysis
    • Statistical Analysis using R
    • Data Analysis and Visualisation in R