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Dr Ben Lambert, who recently achieved his DPhil through the Doctoral Training Centres and the Department of Zoology, is soon to publish a book on Bayesian statistics. Ben wrote the majority of the book alongside his DPhil as well as running courses in Bayesian statistics in the DTC. Here, he explains the journey behind the 'Students Guide to Bayesian Statistics'.

What are you up to these days?

After completing my PhD with Professor Sir Charles Godfray and Dr Ace North on mosquito vectors (2013-2017), I moved to Imperial College London where I now work on the epidemiology of malaria.

How did this book come about?

I have worked in statistical inference for about 8 years; both during my PhD and before that, when I worked as a professional statistician in London. As a sort of (weird) hobby, in 2013, I began to make video lectures on statistics. Over time, this hobby grew into an obsessional habit and now there are over 500 of these videos up on YouTube. In 2014, someone at Sage publishing saw the videos and contacted me to ask if I'd consider writing a book on Bayesian statistics.

What do you hope to achieve with this publication? 

Bayesian statistics has historically been described in texts with a heavy focus on mathematics. I believe that Bayesian inference is a subject rich with intuition, and it is the aim of this book to emphasise the common sense explanations behind this theory. In the book, I don't assume any pre-existing knowledge of probability or classical statistical inference, and go through the Bayesian process from the start, step by step. In doing so, I explain why we need to do computational sampling in many circumstances, and also how these sampling algorithms (known as MCMC) work in practice. I also introduce the reader to an openly-available software tool, called Stan, which allows a user to straightforwardly code up their statistical model and efficiently do parameter inference on it. The book comes with numerous code snippets, videos and interactive online elements which help the reader to better understand the more complex concepts that are encountered.

The book can be purchased from Amazon here: 

More information on the book and my work in Bayesian inference can be found at:

and on the YouTube channel at