If you wish to attend and be invoiced, please contact the CPD Team at [email protected] for information.

This course provides a broad introduction to statistical modelling for health and life science applications. The fundamental role of the statistician as a problem solver will be emphasised and the different stages of the “problem solving” cycle will be considered.

The course will equip you with the theoretical underpinning and computational skills needed for generalized linear regression modelling of health data using the R statistical software. Real-world case studies drawing on our world-class epidemiological research will be used to help you develop an appreciation of modelling strategy and to give you practical experience of interpreting model findings in the context of real health problems.

The course requires familiarity with basic statistical concepts and methods (e.g. descriptive statistics and graphs, t-tests). Some knowledge of R would be advantageous. On 8th May the course has built in a half-day preparatory session on R software to support all delegates in achieving the required level of proficiency in the R software environment.

Who is the course for?

Suitable for Academics, PhDs, industry/NHS, and for those who need to use quantitative models to analyse data to generate evidence or inform policy. This includes researchers and data analysts wanting a practical framework for modern regression modelling of data from clinical trials, or routine health data from electronic health records. 

External Accreditation

CPD points applied for through the Royal College of Physicians.