Overview

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).

You can take this course either online or face to face.  

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

Certificates

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

Cancellations

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

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

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: 25 Mar 2024, 09:36