© 2020, DISCnet            DISCnet is the Data Intensive Science Centre in SEPnet, and an STFC Centre for Doctoral Training;  a collaboration between

the Universities of Southampton, Sussex, Portsmouth, Queen Mary University of London, and Open University

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Statistics and Data Analysis

Description

This 1 day DISCnet event, given by Jonathan Loveday (Sussex), will cover two aspects of Bayesian model fitting: Bayesian Hierarchical Models (BHM) and Approximate Bayesian Computation (ABC). The course runs on 1 April at Queen Mary University of London.

Aim

To acquire the skills needed for analysis of experimental data and model fitting.

 

Objectives

At the end of this course, a successful student will be able to:

  • Fit Bayesian hierarchical models to data, allowing marginalisation over unknown nuisance parameters

  • Use approximate Bayesian computation to allow for likelihood-free inference

Examples

Examples will be given during the course.

Prerequisites / Linked Modules

It is recommended that students have the following software installed on their laptops:

 

Approximate hours:

  • 1030 Arrival Coffee

  • 1100 Intro to Bayesian Hierarchical Modelling and Approximate Bayesian Computation

  • 1230 Lunch

  • 1330 Practical exercises

  • 1700 Close