Bayesian Statistics

The Bayesian Statistics section encourages the development and application of Bayesian methodology in a variety of fields, and inter-disciplinary collaboration. There has been growing interest in Bayesian methods, as it provides a statistical inference procedure with rigorous uncertainty quantification and a principled manner for incorporating prior information. Bayesian methods are becoming increasingly accessible through advancements in modern Bayesian computing and the availability of software packages with an expanding range of functionality.  More recently, Bayesian methods are being harnessed to improve and increase the capabilities of machine learning algorithms.

The Section has organised and promoted various workshops, short courses and seminars held across Australia. The Section has also sponsored visits to Australia for internationally renowned Bayesian researchers to facilitate knowledge-gain and new collaborations.  

Committee

Chair: Chris Drovandi (c.drovandi@qut.edu.au)

Committee members: David Frazier, Clara Grazian,  Sama Low-Choy , Matt Moores and  Sophie Zaloumis

Meet the Bayesian Statistics Section Committee (under construction).

Join Us!

To join the Bayesian statistics section log into your membership profile and tick the relevant box. 

You can also follow us on Twitter


Further Information

Complex problems solved using Bayesian methods

Recommended Reading

Join us


SSA is the home for professionals working in statistics. A place where you belong, connect with others, advance your career and feel inspired.

Our core purpose is to connect you with great people and great opportunities, so you can be successful in your current role and with your career aspirations.

Join now

Powered by Wild Apricot Membership Software