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 any of our two summer schools, but all other courses assume that the basics are understood.
The courses running frequently at CASC are:
Introduction to Statistics and Research Methods
Introduction to Logistic Regression*^
Introduction to Survival/Time-to-Event Data Analysis*^
Assessing Measurement Reliability and Validity
Introduction to Bayesian Analysis*
Analysing 2x2 Tables*
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*~^
Multilevel Data Analysis using R*~^
ANOVA/GLMs with SPSS*
CASC also provide the following summer schools (August, 2017):
* 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.
- Book now on one of our summer schools: Introduction to Statistics and Regressions with R (7th - 11th August) or Introduction to Statistical Thinking and Data Analysis (14th - 18th August)
- Welcome to our new teaching fellow, Dr Dan Green.
- New course dates for the next academic year (from September 2017) to be announced soon.
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 Langan, Dr 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.
The team also features a guest lecturer, George Michaelides, who runs the 'Multilevel Data Analysis using R' course.
From left to right: Dr Dan Green, Prof Angie Wade, Eirini Koutoumanou, Sophie Lee, Dr Dean Langan and Patricia John.
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.