Practical Statistics for Medical Research

Medical statistics plays an essential role in all stages of a quantitative health care research project from design through to analysis and interpretation.

Medical Statistics Online Short Course: 16 - 19 June 2026

About the course

This intensive course covers the essential principles and methods required. Emphasis is on study design, appropriate analysis, and interpretation of results. The underlying concepts of statistical analysis as well as basic and some more advanced analysis techniques are covered. Sessions include lectures and computer practicals. The course has been running for more than 30 years and is taught by experienced medical statisticians.

The computer practicals are conducted using the statistical software Stata. No prior knowledge is required and a license is provided for the duration of the course. Please note that the main purpose of using Stata in this course is to teach statistical concepts through examples, rather than teaching how to use a particular software package.

Organisers and Tutors

The course is jointly organised by UCL Statistical Science and the UCL Joint Research Office. The main speakers and tutors are: Prof Rumana Omar, Dr Mariam Adeleke, Prof Gareth Ambler, Prof Julie Barber, Dr Baptiste Leurent, Dr Menelaos Pavlou and Dr Martin Wiegand (UCL Statistical Science) and Prof Ian White and Prof Andrew Copas (UCL and MRC CTU at UCL).

Dates and times

17 - 20 June 2025. Registration will start at 9:00 on the Tuesday and the course will end by 17:00 on the Friday

Course objectives

The course aims to teach health care researchers the essential elements of research methodology and statistics. The focus is mainly on interpretation and understanding appropriate methodology.

At the end of the course the participants will have gained an understanding of:

The various design possibilities for a research project, and the important considerations for observational studies and randomised trials
The types of data generated in research studies
The most common methods of analysis for categorical and continuous data, including regression methods and survival analysis
When particular methods are appropriate and how to interpret their results
Reviewing and appraising published research

Who should attend?

The course is relevant to all health care professionals or anyone in the health care field who needs to understand, use or carry out health care research studies. Material covered is of an introductory and intermediate level and provides some references and foundation for more advanced techniques. The course assumes a familiarity with the statistical terms used in the medical literature (e.g. P-values and confidence intervals) but does not assume any deep understanding.

Course content

The course is structured into a number of teaching sessions per day, most consisting of lectures followed by a computer workshop. Discussion is very much encouraged.

The following topics are covered:

Day 1	Day 2	Day 3	Day 4
Introduction to Data Analysis	Comparing Groups of Categorical Data	Further Regression Topics	Sample Size Calculations
Design of Observational Studies	Risk, Rates and Odds	Logistic Regression	Overview of Study Design
Design of Randomised Trials	Comparing Groups of Continuous Data	Analysis of Survival Data	Missing Data
Estimation and Hypothesis Testing	Correlation and Linear Regression	Meta-Analysis	Analysis of Correlated Data
			Further Design and Analysis of Trials

Comments from previous participants

"This was an excellent course covering the basics of medical statistics relevant to our role as clinicians. The teaching was excellent - the sessions were delivered at the correct pace and pitched at the right level."
"I felt it was about time I learned more about of the "dark arts" of the profession. This course fulfils that aim brilliantly. Tells you what you need to know, delivered by extremely knowledgeable and approachable experts. Don't change it - it does exactly what it says on the tin!!"
"I was after an overview of statistics so that I could better understand and interpret what it is I read in medical journals and this course was perfect."
"Maintained my interest throughout, engaging speakers, incredibly well designed course."
"I wish I'd been taught this well at medical school!"
"I have been taught Statistics many times in my undergraduate and post graduate studies but this is the first time that I have actually managed to understand it and feel confident to apply it! Thank you
"I have enjoyed the course even though I don't like Statistics!"
"It is so refreshing being taken through these concepts by an experienced statistician, rather than a clinician."
"I really enjoyed the course and feel much more confident than I did before I started."
"The pacing and practical work suited all levels of ability and I feel I really consolidated my overall knowledge throughout the week."
"Inspiring and a real treat, good enthusiastic teachers, superlative in all respects"
"Practicals very well designed, tutors extremely patient and helpful"
"As a surgeon my aim was to get an understanding of which statistics to use for certain studies. I think the course has done this well"
"Very improved understanding of overwhelming statistical theory… course very well organised"
"This is the best medical statistics course I have attended"
"Please think very hard before trying to "improve" this marvellous, no-nonsense, no mumbo-jumbo statistics course!"

Accreditation

This course is expected to be accredited with 23 CPD points (upon approval from the Royal College of Physicians). Participants who complete the course will receive a certificate of attendance.

Course fee

Public Sector: £550 (until 30 April) £650 (from 1 May)
Commercial Sector: £750 (until 30 April) £850 (from 1 May)

Up to 10 award places are available for researchers from UCLH or the UCL Medical School (excluding those on training fellowships). An award offers a reduced registration fee at £200 and the application deadline is 30 January 2026. To apply for an award place, please contact: uclh.biostatistics@nhs.net

Please note that the number of spaces is limited and registrations will close when capacity is reached. The final deadline for registration is 28 May 2026. The fee is to be paid in full at registration, using a debit or credit card via the UCL Online Store.

Cancellation policy

Full refund within 7 days of booking, 80% refund after that.

No refunds will be applied after 1st June 2026.

Location

The course will be held online.

Contact

Please contact Matteo Pacini with any enquiries about the course.