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STAT40950

Academic Year 2023/2024

Adv Bayesian Analysis (online) (STAT40950)

Subject:
Statistics & Actuarial Science
College:
Science
School:
Mathematics & Statistics
Level:
4 (Masters)
Credits:
5
Module Coordinator:
Dr Isabella Gollini
Trimester:
Summer
Mode of Delivery:
Online
Internship Module:
No
How will I be graded?
Letter grades

Curricular information is subject to change.

Bayesian analysis allows us to incorporate uncertainty from multiple sources in a coherent way. We can therefore construct complex models for high dimensional data, however inference for such models may be cumbersome and require specialised approaches. This module will focus on how to build such complex models based on prior beliefs and how to use cutting edge
computational methods to perform fast and accurate inference. How to achieve automatic tuning of algorithms will also be explored.

About this Module

Learning Outcomes:

By the end of this module you will be familiar with the theory and implementation of advanced Bayesian inferential methods that are optimised to explore posterior distributions effectively, including when the likelihood is intractable. You will know which approaches to use and why and will have experience in fitting complex models to highly heterogeneous / structured data.

Student Effort Hours:
Student Effort Type Hours
Lectures

24
Autonomous Student Learning

76
Total

100

Approaches to Teaching and Learning:
Lectures, tutorials, enquiry and problem-based learning.

Requirements, Exclusions and Recommendations
Learning Requirements:

Students will require prior knowledge of Bayesian Statistics and also an advanced understanding of probability and statistics.


Module Requisites and Incompatibles
Required:
STAT40850 - Bayesian Analysis (online)

Incompatibles:
STAT41070 - Bayesian Data Analysis


 

Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade In Module Component Repeat Offered
Continuous Assessment: Mini Projects Varies over the Trimester n/a Alternative linear conversion grade scale 40% No

100

 No

Carry forward of passed components
No
 

Resit In Terminal Exam
Autumn Yes - 2 Hour
Please see Student Jargon Buster for more information about remediation types and timing. 

Feedback Strategy/Strategies

• Group/class feedback, post-assessment

How will my Feedback be Delivered?

Not yet recorded.

Name Role
Ms Mittal Mittal Tutor
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