UCL Great Ormond Street Institute of Child Health


Centre for Applied Statistics Courses

Our statistics courses are designed for anyone who requires an understanding of research methods and statistical analyses. The training we provide helps non-statisticians to interpret published research and undertake their own research studies.

Extensive notes are provided for all courses, and teaching is interspersed with practical examples and activities throughout the day(s) 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 Statistics and Research Methods), or our summer schools, but all other courses assume that the basics are understood.

Our courses usually take place weekdays between 10.00am and 4.30pm. Selected evening dates that run between 5.30pm and 8.15pm are also available for some of our more popular courses, including Introduction to Statistics and Research MethodsIntroduction to R and Introduction to SPSS.

The courses running frequently at CASC are:

Classroom-based courses:
Introduction to Statistics and Research Methods - plus after dark dates!
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*
Analysis of 2x2 Tables*
Introduction to Latent Class Analysis* - NEW COURSE for 2018!

Statistics software courses:
Introduction to SPSS* - plus after dark dates!
Introduction to R* - plus after dark dates!
Further Topics in R*~
Introduction to Stata*

Mixed courses with statistical theory and software:
Introduction to Meta-analysis* (with optional R workshop~)
Sample Size Estimation and Power Calculations with Excel*
Introduction to Dealing with Missing Data* (with optional SPSS workshop)
Introduction to Regression Analysis* (with optional SPSS workshop)
Overview of Regressions with R*~^

Summer Schools (August 2018)

Introduction to Statistical Thinking and Data Analysis
Introduction to Statistics and Regressions with R

* 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.

Click here for a list of all our courses in chronological order

Who are we?

The Centre for Applied Statistics Courses (CASC) comprises Director of CASC Professor Angie Wade, Senior Teaching Fellow Miss Eirini Koutoumanou, Teaching Fellows Dr Dean LanganDr Dan Green and Sophie Lee, and administrator Patricia John. 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




For general queries/payments, call us on: +44 (0) 20 7905 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.

Centre for Applied Statistics Courses (CASC), UCL Great Ormond Street Institute of Child Health, 30 Guilford Street, London, WC1N 1EH

Where are we based? 

CASC courses are typically based within 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 easy walking distance.

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.