Short courses


Bayesian Analysis: an Introduction

  • 9:30am to 5pm
  • 1 day
  • 12 Jun 2024


This online short course focuses on the principles of Bayesian data analysis.

You'll learn to apply Bayesian methods to your own research and understand other people's results using Bayesian analysis.

This course is run by UCL's Centre for Applied Statistics Courses (CASC), part of the UCL Great Ormond Street Institute of Child Health (ICH).

Course content

The workshop will help you to understand and critically evaluate published research that uses Bayesian analysis.

It will also give you the confidence to implement Bayesian concepts.

You'll learn about:

  • the differences between frequentist and Bayesian methods
  • the important features of Bayesian methods and how best to define them (such as priors and likelihoods)
  • how best to report or explain applied Bayesian analysis
  • using WinBugs to apply Bayesian analysis

Who this course is for

The course is aimed at professionals who want to be able to understand the fundamental principles of Bayesian analysis to assist their own research as well as interpreting other people's findings.

There are no pre-requisites but it's desirable to have a basic knowledge of statistics, i.e. notion of statistical inference, p-values and confidence intervals.

Learning outcomes

By the end of this course you should be able to:

  • understand the differences between frequentist and Bayesian methods
  • understand the important features of Bayesian methods and how best to define them (e.g. priors and likelihoods)
  • interpret Bayesian analysis results presented by others
  • know how best to report/explain applied Bayesian analysis
  • use WinBugs to apply Bayesian analysis

Cost and concessions

The fees are as follows:

  • External delegates (non UCL) - £150
  • UCL staff, students, alumni - £75*
  • ICH/GOSH staff and students - free    

* valid UCL email address and/or UCL alumni number required upon registration


You can request a certificate of attendance for this course once you've completed it. Please send your request to ich.statscou@ucl.ac.uk

Include the following in your email:

  • the name of the completed course for which you'd like a certificate
  • how you'd like your name presented on the certificate (if the name/format differs from the details you gave during registration)


Read the cancellation policy for this course on the ICH website. Please send all cancellation requests directly to the course administrator

Find out about other statistics courses

CASC's stats courses are for anyone requiring an understanding of research methodology and statistical analyses. The courses will allow non-statisticians to interpret published research and/or undertake their own research studies.

Find out more about CASC's full range of statistics courses, and the continuing statistics training scheme (book six one-day courses and get a seventh free.) 

Course team

Dr Eirini Koutoumanou

Dr Eirini Koutoumanou

Eirini has a BSc in Statistics from Athens University of Economics and Business and an MSc in Statistics from Lancaster University (funded by the Engineering and Physical Sciences Research Council). She joined UCL GOS Institute of Child Health in 2008 to develop a range of short courses for anyone interested in learning new statistical skills. Soon after, CASC was born. In 2014, she was promoted to Senior Teaching Fellow. In 2019, she successfully passed her PhD viva on the topic of Copula models and their application within paediatric data. Since early 2020 she has been co-directing CASC with its founder, Emeritus Professor Angie Wade, and has been the sole Director of CASC since January 2022. Eirini was promoted to Associate Professor (Teaching) with effect from October 2022.

Dr Chibueze Ogbonnaya

Dr Chibueze Ogbonnaya

Since joining the teaching team at CASC in February 2019, Chibueze has contributed to the teaching and development of short courses. He currently leads and co-leads short courses on MATLAB, missing data, regression analysis and survival analysis. Chibueze has a BSc in Statistics from the University of Nigeria, where he briefly worked as a teaching assistant after graduation. He then moved to the University of Nottingham for his MSc and PhD in Statistics. His research interests include functional data analysis, applied machine learning and distribution theory.

Learner reviews

"Really excellent and accessible introductory course - covered a lot in one day."

"I would like to thank the course facilitator, who was very friendly, approachable and open to questions."

"Overall I thought it was a good event, well prepared and with good content. It was transmitted clearly. I think Eirini did a great job putting across a complicated subject very simply. I will definitely recommend the course to colleges."

"The course was very well delivered and I was glad to attend."

Course information last modified: 13 May 2024, 11:28