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Bayes for Beginners - Workshop 1

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Course Information

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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.

Booking OptionFee
Full Workshop Fee £20.00
Full Workshop Fee - Postgraduate student rate £10.00

 

Course Code

ESRC Workshop 1

Course Date

6th April 2017

Places Available

Course Leader

Mark Andrews

Course Fee

£20.00
Course Description

Time: 9 am - 5 pm

Location: Room 424, Chaucer building, Nottingham Trent University, NG1 5LT

Prerequisites

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

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’s 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, and calculating marginal likelihoods for comparing distinct probabilistic models.

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).

Indicative reading

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

Baguley, T. (2012). Serious stats: A guide to advanced statistics for the behavioral sciences. Palgrave Macmillan. [especially Chapter 11]

Bursaries

Bursaries are available to apply for, to assist with costs associated with attending this workshop. Please see Bookings tab for further information. Please note that only PhD students who attend UK HE institutions are eligible to apply for this bursary.