# Bayesian Data Analysis Workshop Series

## Bayes for Beginners - Workshop 1

Workshops

This workshop aims to be a general introduction to Bayesian data analysis and how it differs from the more familiar classical approaches to data analysis.

• From: Thursday 31 March 2016, 9 am
• To: Thursday 31 March 2016, 5 pm
• Location: 424, Chaucer building, Nottingham Trent University, City Campus, Goldsmith Street, Nottingham, NG1 5LT

## Event details

Workshop content

This workshop aims to be a general introduction to Bayesian data analysis and how it differs from the more familiar classical approaches to data analysis.

We will start by providing a brief historical overview of statistical inference and introduce Bayes's theorem. The fundamental concepts of Bayesian statistical inference will follow, contrasted with frequentist methods of inference.

To provide a bridge between Bayesian and classical methods, we will describe likelihood function approaches to inference and introduce both the likelihood principle and the law of the likelihood as the general precepts of likelihood-based inference.

During this workshop, there will also be practical exercises including:

• using Bayes' rule to calculate posterior probabilities and posterior distributions
• choosing priors in probabilistic models and illustrating their role on the posterior distributions
• calculating likelihood ratios and Bayes factors to compare evidence for different parameters in a probabilistic model
• calculating marginal likelihood for comparing distinct probabilistic models.

Prerequisites

The only prerequisite for the initial workshop will be familiarity with the standard repertoire of statistical tools that are used in psychology and other social sciences – for example, tests such as t-tests, ANOVA, correlation and regression – as well as fundamental concepts of classical statistical inference such as p-values and null hypothesis significance tests.

Learning outcomes

On completion of this workshop, attendees will be familiar with the philosophical and practical issues of both the classical and Bayesian approaches to statistical inference. They should be able to apply this knowledge to simple practical research questions and be able to engage with work using Bayesian methods in their area (e.g. as a reviewer or editor).

Dienes, Z. (2008). Understanding psychology as a science: An introduction to scientific and statistical inference.

Baguley, T. (2012). Serious stats: A guide to advanced statistics for the behavioural sciences. Palgrave Macmillan

Bursaries

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

## Programme

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

### Room/Building:

424, Chaucer building