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Bayesian Data Analysis Workshop Series

Doing Bayesian Data Analysis in Psychology and the Social Sciences - Workshop 2

Newton atrium roof

This workshop aims to provide a solid theoretical and practical foundation for real-world Bayesian data analysis in psychology and social sciences.

  • From: Friday 1 April 2016, 9 am
  • To: Friday 1 April 2016, 5 pm
  • Location: 424, Chaucer building, Nottingham Trent University, City Campus, Goldsmith Street, Nottingham, NG1 5LT
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Event details

Workshop content

This workshop aims to provide a solid theoretical and practical foundation for real-world Bayesian data analysis in psychology and social sciences.

It will focus primarily on the linear statistical models and so-called conjugate prior distributions. The reason for this focus is twofold. First, linear models – which include t-tests, ANOVA, and linear regression models – are the core of the standard repertoire of statistical models with which our audience will be familiar. Studying the Bayesian counterparts of these approaches will therefore be a natural transition.

Second, Bayesian inference in linear models with conjugate priors is analytically tractable, and this means, amongst other things, that we can use relatively simple formulae to calculate the posterior distribution over the parameters and to make predictive inferences. This allows us to illustrate the general nature of Bayesian inference quickly and easily, postponing the computational and practical complications that arise as a consequence of performing Monte Carlo-based numerical approaches to inference.

In practical terms, this workshop will involve the use of the R statistical computing environment both to calculate posterior distributions in linear models and to graphically illustrate them. Indeed, graphically illustrating, for example, how the posterior distribution is a weighted average of the prior and likelihood functions and how the contribution of the likelihood function grows rapidly with increasing data, provides compelling intuitive insight into the nature of Bayesian inference.


The prerequisites for this workshop are fulfilled by workshop 1: Bayes for Beginners. They include a general understanding of the core concepts of Bayesian statistical inference, and the general distinction between classical and Bayesian statistical methods.

Learning outcomes

On completion of this workshop, we expect attendees to be able to confidently perform and understand the Bayesian counterparts to many of the models with which they would already be familiar. They will also become familiar with new concepts – conjugate priors, posterior predictive distributions, and marginalised likelihood functions – that arise only in the context of Bayesian data analysis.

Indicative reading

Lee, P. M. (2004). Bayesian Statistics: An Introduction. London, UK: Hodder Arnold.

Gelman, A., Carlin, J. B., Stern, H. S., Rubin, D. B. (2003). Bayesian data analysis (2nd ed.). Chapman & Hall.


Bursaries are available  to assist with costs associated with attending this workshop. Please see Bookings tab for further information on how to apply.


The detailed programme for the day will be published a little closer to the time.

Booking information

Please note that this workshop is now fully booked.

Workshop fees

Please note that all prices are inclusive of VAT.

Booking OptionFee
Full Workshop Fee £20
Full Workshop Fee - Postgraduate student rate £10

Location details


424, Chaucer building


Nottingham Trent University
City Campus
Goldsmith Street

Past event

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