Short courses


R: Further Topics

  • 9:30am to 1pm
  • 2 days


This course is for those familiar with the basics of the statistical software R and want to learn how to use R's advanced features.

You should have basic knowledge of R programming and statistics (e.g. mean, median, confidence intervals).

This course takes place online, over two mornings (9:30am to 1pm). 

This course is run by UCL's Centre for Applied Statistics Courses (CASC), part of the UCL Great Ormond Street Institute of Child Health (ICH).

Course content

This course will cover the following topics:

  • An introduction to the Rstudio software
  • Organising and merging multiple datasets
  • Conditional (TRUE of FALSE) statements
  • Conditional commands (if, if else, etc.)
  • Loops
  • Creating your own function
  • An introduction to ggplot2 (as time allows)

    Computers and software

    You'll need to have R and Rstudio installed on your computer (installation guidelines will be made available two weeks before the course).

    Learning outcomes

    By the end of this course you should be able to:

    • use the software Rstudio for R programming
    • work with multiple datasets that may be linked and part of the same analysis
    • make R code more generalisable and responsive to changes in the data
    • use loops to make code more concise and understand when they are required
    • create new R functions


    You can request a certificate of attendance for this course once you've completed it. Please send your request to ich.statscou@ucl.ac.uk

    Include the following in your email:

    • the name of the completed course for which you'd like a certificate
    • how you'd like your name presented on the certificate (if the name/format differs from the details you gave during registration)

    Cost and concessions

    The fees are as follows:

    • External delegates (non UCL) - £200
    • UCL staff, students, alumni (including ICH/GOSH) - £100*

    * valid UCL email address and/or UCL alumni number required upon registration


    Read the cancellation policy for this course on the ICH website. Please send all cancellation requests to the course administrator.

    Find out about other statistics courses

    CASC's stats courses are for anyone requiring an understanding of research methodology and statistical analyses. The courses will allow non-statisticians to interpret published research and/or undertake their own research studies.

    Find out more about CASC's full range of statistics courses, and the continuing statistics training scheme (book six one-day courses and get a seventh free.)

    Course team

    Dr Chibueze Ogbonnaya

    Dr Chibueze Ogbonnaya

    Since joining the teaching team at CASC in February 2019, Chibueze has contributed to the teaching and development of short courses. He currently leads and co-leads short courses on MATLAB, missing data, regression analysis and survival analysis. Chibueze has a BSc in Statistics from the University of Nigeria, where he briefly worked as a teaching assistant after graduation. He then moved to the University of Nottingham for his MSc and PhD in Statistics. His research interests include functional data analysis, applied machine learning and distribution theory.

    Dr Eirini Koutoumanou

    Dr Eirini Koutoumanou

    Eirini has a BSc in Statistics from Athens University of Economics and Business and an MSc in Statistics from Lancaster University (funded by the Engineering and Physical Sciences Research Council). She joined UCL GOS Institute of Child Health in 2008 to develop a range of short courses for anyone interested in learning new statistical skills. Soon after, CASC was born. In 2014, she was promoted to Senior Teaching Fellow. In 2019, she successfully passed her PhD viva on the topic of Copula models and their application within paediatric data. Since early 2020 she has been co-directing CASC with its founder, Emeritus Professor Angie Wade and has been the sole Director of CASC, since January 2022.

    Course information last modified: 30 Nov 2022, 16:01