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Introduction to Bayesian Analysis

21 March 2025, 9:30 am–5:00 pm

This course focuses on the principles of Bayesian analysis with the aim to enable participants to apply Bayesian methods on their own research and understand other people's results via Bayesian analysis.

Event Information

Open to

All

Availability

Yes

Cost

£150.00

Organiser

Centre for Applied Statistics Courses
+44 (0) 20 7905 2768

Book Now (Hybrid)

Note: This course will be delivered in hybrid mode, i.e. the in-person lecture will be transmitted live on zoom. The face-to-face part of the hybrid courses will go ahead conditional on at least 5 participants registering for this mode of delivery. Few classes may be delivered exclusively online, so please check under the Future dates tab for clarification. The online part of the class will be supported by its own dedicated teaching staff (along with the lead lecturer), therefore participants can expect the same level of group and individual support as the face-to-face class. You will be able to choose your preferred mode of attendance (face-to-face or online) during registration.

Additionally, we now offer this as a self-paced, online course that you can register for and start at any time. Click below under the 'Online/Self-Paced Materials' tab to register and gain access:

Details

Bayesian analysis is an alternative approach to the statistical techniques that are commonly used throughout most of the research world for the analysis of data. It's core principle stems for the idea that experiments are not abstract devices, hence knowledge existent prior to an experiment should be incorporated formally and openly in the analysis.

This course is aimed at professionals who want to be able to understand the fundamental principles of the Bayesian analysis in order to assist their own research as well as interpret other people's findings. By the end of this workshop, delegates should be able to understand and critically evaluate published research that has used Bayesian analysis as well as be confident to implement Bayesian concepts in their own research.

It is desirable for the course participants to have basic knowledge of statistics, i.e. notion of statistical inference, p-values and Confidence intervals.

Fees

Course fees (live)

Below are the course fees for all courses delivered live either face-to-face, or through online video feed.

External Delegates (Non-UCL)£150.00
UCL Staff and Students£75.00 *
UCL Alumni£75.00
Staff and Doctoral Students from ICH/GOSHFREE †

* Valid UCL email address and/or UCL alumni number required upon registration. Please note, this category does not include hospital staff unless you hold an official contract with the university.

† Limited free spaces available. If there are no free places remaining, Staff and Doctoral Students from ICH/GOSH can still register at the UCL rate.

CancellationsCancellation Policy

Course Fees (self-paced)

Below are the fees for access to the online, self-paced version of this course.

External Delegates (Non-UCL)

£75.00 (inc. VAT)

UCL Staff, Students, Alumni *

£37.50 (inc. VAT)

Staff from ICH/GOSH, and doctoral students *

FREE †    

* A valid UCL email address and/or UCL alumni number required. Please note, this category does not include hospital staff unless you have a formal affiliation with the university. To get this discount, please email ich.statscou@ucl.ac.uk to confirm your eligibility and receive a code that can be entered at the checkout.

† If you are a doctoral student from UCL, you can get access to this, and all other self-paced courses developed by CASC by filling in this online form.

Future Dates
DatesTimeApply
21st March 20259.30am - 17.00pmBook Now

^We recommend logging in 10 minutes prior to the scheduled start time to access materials and ensure the course can start promptly at 9.30am.

Online/self-paced materials

An online, self-paced version of this course is available that includes the following materials:

  • Full electronic notes
  • Short lecture videos (recorded outside of the classroom) that follow closely with the notes
  • Accessible materials with alternative text for images, and captions/transcripts for each video
  • Interactive multiple choice quizzes
  • Extended practical exercises (with solutions) for further comprehension

Support: The course includes unlimited support through a forum that will be manned by one of our teaching fellows. We aim to provide responses to all questions on Tuesday and Friday each working week. Note that questions can only relate directly to the course materials and should not be used as a consultancy service for your own projects.

Personalised certificates will be generated automatically on completion.

UCL extend: The link below leads to the UCL extend store where this self-paced course is available for purchase. If you are eligible for a discount, then please email ich.statscou@ucl.ac.uk to receive a voucher code that can be used on checkout. UCL delegates should use their university email address to register, and external delegates can use any other account. 

Click to register (online/self-paced)

Alternatively, if you are a doctoral student from UCL, you can get access to this, and all other self-paced courses developed by CASC by filling in this online form.

Feedback

"Very well designed and conducted courses. Very interesting and clear. I definitely recommend."

"I decided go to London from Sao Paulo/Brazil to visit the city and to take this course. The result was that I'm happy with this great introduction of Bayesian Analysis and I'll recommend this course to all my colleagues in Brazil."

"Always taught well, I like the professors friendly manner and that she doesn't talk down to you and understands that we want to know the concepts not the maths."

"I think the course was great and the prof was very good."

"The speaker came off as incredibly knowledgeable about the topic and gave succinct and clear answers to the questions being asked. The materials were also nicely organised, and the format of the notes will (I believe) make it easy to return to the material at a later point in time. This was my first of these stats courses, and I would definitely attend another."

"The presenter was excellent and explained everything very clearly."