Introduction to Bayesian Modelling and Analysis – Adelaide

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Professor Kerrie Mengersen and the South Australian Branch of the Statistical Society are pleased to present the workshop

Introduction to Bayesian Modelling and Analysis

in Adelaide on 21-22 September 2016.

 

Where

University of Adelaide

Includes materials and refreshments.

Bookings close on 14 September 2016.

Introduction to Bayesian Modelling and Analysis

 

About the Presenter

Professor Mengersen is a Professor of Statistics in the School of Mathematical Sciences and Institute for Future Environments at QUT. She has around 25 years of experience in statistical modelling, analysis and computation, with particular focus on applications in health, environment and industry. Her expertise includes analysis and integration of complex datasets, encapsulation and effective use of expert information, spatio-temporal analysis and complex systems modelling. In addition to academic outputs comprising over 250 journal articles, she has a continuous record of commercial consultancies with selected relevant clients including Corrs Chambers Westgarth (risk), Goronickel (design), Qld Environmental Protection Agency and Healthy Waterways (water quality), Port of Brisbane (prediction), Qld Dept Natural Resources (environmental statistical modelling and analysis), Western Mining Company (analysis) and Dairy Australia (triple bottom line sustainability). Professor Mengersen is a Deputy Director of the ARC Centre of Excellence in Mathematical and Statistical Frontiers for Big Data, Big Models and New Insights (ACEMS), and an ARC Laureate Fellow.

 

About the course

Overview

Bayesian modelling and data analysis are becoming a standard part of the statistical toolkit. Its appeal includes the availability of hierarchical models for better describing complex systems, the use of priors to describe uncertainty and include external information in the analysis, and the direct probabilistic interpretation of the results.

While simple Bayesian models can be analysed analytically, most analysis is via Monte Carlo methods such as Markov chain Monte Carlo (MCMC). There is a great range of MCMC and other algorithms available now for Bayesian computation.

This two-day course introduces the practising statistician to Bayesian analysis. The course is strongly practical, with emphasis on understanding the fundamental concepts, modelling in a Bayesian context, using MCMC and ‘doing’ Bayesian analysis via the software packages R and WinBugs.

Please note that this course is introductory. It assumes some knowledge of statistics but no knowledge of Bayesian or MCMC approaches.

Feedback from our workshop with Professor Mengersen on  Intermediate Bayesian Statistics in Melbourne in July 2016: “It was a great workshop. The presenter was excellent.”

 

IT Requirements

Participants are requested to bring a laptop with the following software loaded:

– R (freeware statistics program)

– WinBugs (freeware program)

 

Course Outline

The following topics will be covered:

  • What is Bayesian Statistics
  • Priors, models & results
  • Common MCMC algorithms
  • Model fit & model choice
  • Role & formulation of priors
  • Examples of different types of models
  • Reporting of Bayesian analysis results, with examples from published literature

 

Tentative Course Timetable (subject to change)

Day 1

9.00   – 10.30am                    Overview of Bayesian Modelling

10.30 – 10:50am                    Morning tea

10:50 – 12.30pm                    Overview of MCMC

12.30 – 1.30pm                     BYO Lunch

1.30   –  3.10pm                     Bayesian generalized linear models and Practical Session 1

3.10   –  3.30pm                    Afternoon tea

3.30   –  5.00pm                    Practical Session 2

Day 2

9.00   – 10.30am                    Bayesian latent variable modelling

10.30 – 10:50am                    Morning tea

10:50 – 12.30pm                    Practical session 3

12.30 – 1.30pm                     BYO Lunch

1.30   –  3.10pm                     Algorithms: MCMC and more

3.10   –  3.30pm                     Afternoon tea

3.30   –  5.00pm                     Writing up a Bayesian analysis

 

Target Audience

Practising statisticians wanting to learn and apply the fundamentals of Bayesian analysis or researchers in other disciplines with a statistical knowledge equivalent to one year of undergraduate study.

Basic statistical knowledge, and statistical computing, but no knowledge of Bayesian methods.

 

Learning Objectives

Attendees will gain a basic understanding the fundamental concepts, modelling in a Bayesian context, using MCMC and ‘doing’ Bayesian analysis via the software packages R and WinBugs. Participants will be introduced to a range of models for describing complex data and the application of these models to real problems.

 

Course Costs:

Early Bird (until 26 August 2016)

SSA Members – $400

SSA Student Members** – $250

Non-SSA Members – $640

Non-SSA Student Members** – $280

 

From 27 August 2016

SSA Members – $480

SSA Student Members** – $300

Non-SSA Members – $710

Non-SSA Student Members** – $330

** Proof of Valid University ID required

Registrations close strictly on 14 September 2016. Should places be available after this date late registrations may be accepted. Late registrations will incur a $100 late registration fee.


Travel Expenses

Occasionally workshops have to be cancelled due to a lack of subscription. Early registration ensures that this will not happen. Please contact the SSA Office before making any travel arrangements to confirm that the workshop will go ahead, because the Society will not be held responsible for any travel or accommodation expenses incurred due to a workshop cancellation.


Cancellation Policy

Cancellations received prior to Wednesday, 14 September 2016 will be refunded, minus a $20 administration fee.

From 14 September 2016 no part of the registration fee will be refunded. However, registrations are transferable within the same organisation. Please advise any changes to [email protected].

Introduction to Bayesian Modelling and Analysis - Adelaide
When: 21/09/2016 - 22/09/2016
Time: 9:00 am - 5:00 pm
Cost: from $300 (students)
Location: Ingkarni Wardli Building Basement,
Basement Room B15 CAT Suite 1,
University of Adelaide,
SA
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