Cost: £200 *
*Concessions may be available
This one-day course is aimed at researchers who want to learn how to use the statistical software R.
You'll be introduced to the R interface and the R language in order to conduct statistical analysis - from reading-in your datasets to performing all mainstream statistical tests.
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).
The topics covered using R will include the following:
- Introduction to the R platform and interface
- Introduction to basic scripting commands
- Input of data sets
- Summary measures
- Graphical displays
- Statistical tests (parametric and non-parametric)
- Add-ons and packages in R
- Help in R
Eligibility and pre-course preparation
You'll be expected to have a basic understanding of common statistical tests and concepts as these won't be taught during this workshop.
You can use the centre's computers, or bring your own laptop with R installed
(you'll be sent step-by-step installation guidelines two
weeks before the course).
By the end of this course you should be able to:
- feel more familiar with the R interface and language
- read existing datasets into R or create new ones
- edit and save changes in existing data
- summarise and graphically display data
- perform all conventional statistical analysis tests
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
Prices include printed course materials, refreshments and lunch.
You can request a certificate of attendance for this course once you've completed it. Please send your request to firstname.lastname@example.org
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)
You can cancel your booking up to five working days before the start of the course for a full refund, but please give as much notice as possible. Places cancelled or changed after this point won't be eligible for a refund. 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.)
Sign up for short course announcements: Subscribe to the UCL Life Learning newsletter to receive news and updates on courses in your chosen area. (For updates on a specific course, contact the administrator - see 'Contact information'.)
Eirini Koutoumanou - Course Lead
Eirini joined GOS ICH in 2008 as the first CASC Teaching Fellow and was promoted to Senior Teaching Fellow in 2014. She has a Bachelor’s degree in Statistics from the Athens University of Economics and Business and a Master's degree in Statistics from Lancaster University, and she's currently studying for a PhD at ICH. Eirini started teaching at ICH straight after her student days, putting into practice and further developing her passion for statistics teaching. She's played an instrumental role in the formation of CASC and hopes to see it develop further.
Dr Dean Langan - Course Lead
Dean joined GOS ICH in 2015 as a Teaching Fellow in CASC. He has a Bachelor’s degree in Mathematics from University of Liverpool, a Master's degree in Medical Statistics from University of Leicester, and a PhD from University of York for his research in statistical methods for random-effects meta-analysis. He's worked as a statistician on a number of clinical trials related to stroke and myeloma at the Clinical Trials Research Unit in Leeds. His specialist areas include statistical methods for meta-analysis, R programming, clinical trial methodology and research design.
“Superb teaching - thank you! Progressed at the right pace.”
“Great trainer who didn't assume anything about peoples' pre-knowledge”
“Really useful introduction - much better than trying to read about it yourself. Will try to follow on with regression in R to get more teaching on the package.”
“Very enjoyable! Good examples.”
“Excellent style of teaching: covered basics but at very good pace and without being patronising. Thank you”
“Great delivery by the presenter. Very clear and examples were very understandable across disciplines. The content was very clear. Help and explanations were also very clear.”
"Very practical tips for using R were enormously helpful, and not the kind of thing that the textbooks seem to cover at all well."
“A very, very good course, led by 2 very good facilitators/teachers. Everything was clear and delivered efficiently and on time. Really great course and I would highly recommend.”
Course information last modified: 04 Oct 2017, 09:34