We provide short courses in research methods and statistical analyses for anyone wanting to interpret or undertake their own research. Everyone is welcome to attend, including those based outside UCL.
Extensive notes are provided for all courses, and teaching is interspersed with practical examples and activities throughout courses to ensure that everyone has understood the key principles. We strive to create a relatively informal learning atmosphere, where participants are not afraid to ask questions or voice any confusion.
No prior statistical knowledge is assumed for our introductory course (Introduction to Research Methods and Statistics), or our summer schools, but all other courses assume that the basics are understood. Our courses usually take place on weekdays during typical office-hours and selected evening dates may also be available for certain courses depending on timetable availability.
We anticipate to deliver all short courses (or definitely the vast majority of them) in hybrid mode in 2023. This means that the lecture will be delivered in a classroom or computer room as appropriate (conditional to a minimum of 5 participants attending the face-to-face lecture) which will be concurrently transmitted live to an online class via zoom. Participants will be able to choose their preferred method of attendance (face-to-face or online) during the registration process. Please see our events calendar for a chronological list of our statistics courses (note: this calendar only shows the most imminent date for each course).
We have a new online, self-paced course for Introduction to Dealing with Missing Data, which includes forum support and interactive quizzes. Other self-paced courses are avaiable (see list below marked with a § symbol)
A new online training programme developed through CASC is available for doctoral students based in the School of Life and Medical Sciences. This includes all the above self-paced courses. If you would like access, please complete this online form.
The courses running frequently at CASC are:
- Hybrid Winter school: Introduction to Statistics with R (12-16 February 2024)
Hybrid Summer school: Introduction to Statistics with R (New date to be confirmed)
- Introduction to Research Methods and Statistics ✝§
- Critical Appraisal §
- Introduction to Logistic Regression *^§
- Introduction to Poisson Regression *^
- Introduction to Survival/Time-to-Event Data Analysis *^
- Assessing Measurement Reliability and Validity *
- Introduction to Bayesian Analysis *§
- Chi-square and Beyond for 2x2 Tables *
- Introduction to Latent Class Analysis *
Theory-based courses (with an optional software workshop):
- Introduction to Meta-Analysis *§ (with optional R workshop~)
- Introduction to Dealing with Missing Data *§ (with optional R/SPSS/Stata workshop)
- Introduction to Regression Analysis *§ (with optional SPSS/R/Stata workshop)
Mixed courses with integrated statistical theory and software:
- Sample Size Estimation and Power Calculations with Excel *✝
- Overview of Regressions with R *~^
- ANOVA/GLMs with SPSS *
Statistics software courses:
- Introduction to SPSS *✝
- Introduction to R *✝§
- Further Topics in R *~
- Introduction to Stata *✝
- Introduction to Data Analysis using MATLAB
Alternatively, please see the events calendar for a chronological list of statistics courses running at ICH (note: this calendar only shows the most imminent date for each course).
* Knowledge of basic statistical concepts is required/beneficial; we recommend the Introduction to Research Methods and Statistics course if you have little/no previous statistics experience; this course offers a good basis for all other CASC courses.
~ requires prior knowledge/experience of the R software.
^ We recommend attending the Introduction to Regression Analysis course first if you have no prior experience of regression analyses.
✝ Evening dates often available for this course
§ Self-paced online materials available for purchase
- Who are we?
The Centre for Applied Statistics Courses (CASC) was founded in 2008 by Emeritus Professor Angie Wade, and it currently comprises of Director and Associate Professor Dr Eirini Koutoumanou, Lecturer Dr Dean Langan, and Associate Lecturers Dr Chibueze Ogbonnaya, Dr Catalina Suarez-Rivera and Dr Manolis Bagkeris. We receive administrative support from the ICH events team. Based within UCL Great Ormond Street Institute of Child Health, we run a variety of higher degree and short courses for non-statisticians.
- Contact us
Please see our FAQ page before making an enquiry about our courses.
Recommended for general queries/payments:
For general enqueries/payment: +44 (0) 207905 2768. To contact a teaching fellow about the contents of a course, call us on: +44 (0) 77 30405 980
** Please note that the mobile phone is manned by teaching staff so we may not be able to answer your call straight away, but feel free to leave a message or forward your query on by email where it may be more quickly responded to.
- Where are we based?
Our courses are usually based near to GOS Institute of Child Health; the nearest underground station is Russell Square on the Piccadilly line. Holborn, Chancery Lane, Euston and Kings Cross stations are all within walking distance. However, most advertised courses will be run in a hybrid mode (online and in-person attendance).
- Visitors to the GOS Institute of Child Health
Great Ormond Street Institute of Child Health welcome visitors to take part in all of our teaching activities.
Visitors are responsible for securing their own accommodation. If accommodation is required this should be arranged before arrival and funded independently. Please visit the interactive map of hotels nearby.
- Free online materials
The following supplementary materials and tools are freely available online as written by the CASC team. These are free for everyone, even if you are not enrolled on any of our short courses.
- Spreadsheets for analysing 2x2 tables that compliment our one-day course 'Chi-square and Beyond for 2x2 Tables'
- Spreadsheets for doing sample size calculations, related to the course 'Sample Size Estimation and Power Calculations with Excel'
Additionally, here is a list of Moodle pages for all courses (only accessible with a password given on registration)