- Homepage
- Key Information
- Students
- Taught programmes (UG / PGT)
- Student Services and Procedures
- Student Support
- Events and Colloquia
- International Students
- Students as Change Agents (SACA)
- Student Staff Liaison Committees (SSLC)
- The Exeter Award
- Peer Support
- Skills Development
- Equality and Diversity
- Athena SWAN
- Outreach
- Living Systems Institute Webpage
- Alumni
- Info points and hubs
- Inbound Exchange Students
- Staff
- PGR
- Health and Safety
- Computer Support
- National Student Survey (NSS)
- Intranet Help
- College Website
ECMM459 - Statistical Modelling (2023)
MODULE TITLE | Statistical Modelling | CREDIT VALUE | 15 |
---|---|---|---|
MODULE CODE | ECMM459 | MODULE CONVENER | Dr Tinkle Chugh (Coordinator) |
DURATION: TERM | 1 | 2 | 3 |
---|---|---|---|
DURATION: WEEKS | 7 |
Number of Students Taking Module (anticipated) | 90 |
---|
*** This module is a “professional” module intended to be taught in a short-fat format based around 3-day teaching blocks, as part of the MSc Data Science (Professional) programme. ***
In this course we look at the concepts and methods of modern statistics in greater detail. The course will cover various topics in statistical modelling with Bayesian flavor, including generalised linear models, Hierarchical statistical models, Generative and Discriminative models, Hidden Markov models, use of Markov Chain Monte Carlo and Gaussian processes. The module will include practical application of these techniques as well as theoretical underpinnings and model choice.
Pre-requisites: ECMM456 Fundamentals of Data Science (Professional)
Co-requisites: None.
The aim of this module is to introduce you to modern methods in statistics, both conceptually and computationally.
Scheduled Learning & Teaching Activities | 34.00 | Guided Independent Study | 46.00 | Placement / Study Abroad | 0.00 |
---|
Category |
Hours of study time |
Description |
Scheduled learning and teaching activities |
20 |
Lectures |
Scheduled learning and teaching activities |
14 |
Workshop/Practical classes in a computer lab |
Guided independent study |
46 |
Coursework preparation and self-study |
|
Form of Assessment |
Size of Assessment (e.g. duration/length) |
ILOs Assessed |
Feedback Method |
Exercise/Quiz |
1h x 4 |
All |
Written |
Coursework | 100 | Written Exams | 0 | Practical Exams | 0 |
---|
Form of Assessment |
% of Credit |
Size of Assessment (e.g. duration/length) |
ILOs Assessed |
Feedback Method |
Coursework report |
100 |
2000-3000 words |
All |
Written |
Original Form of Assessment |
Form of Re-assessment |
ILOs Re-assessed |
Time Scale for Re-assessment |
Coursework report |
Coursework report |
All |
Ref/Def period |
Reassessment will be by coursework in the failed or deferred element only. For referred candidates, the mark will be capped at 50%. For deferred candidates, the mark will be uncapped.
information that you are expected to consult. Further guidance will be provided by the Module Convener
Reading list for this module:
Type | Author | Title | Edition | Publisher | Year | ISBN | Search |
---|---|---|---|---|---|---|---|
Set | Gelman, A., Carlin, J., Stern, H., Dunson, D., Vehtari, A. and Rubin, D. | Bayesian data analysis | 3rd | CRC | 2008 | [Library] | |
Set | Gamerman, D. and Lopes H. F. | Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference | CRC Press | 2006 | [Library] | ||
Set | Banerjee, S., Bradley, P. Carlin, A.& Gelfand, E. | Hierarchical Modeling and Analysis for Spatial Data | CRC Press | 2014 | [Library] | ||
Set | Donovan, Therese and Mickey, Ruth M. | Bayesian Statistics for Beginners: a step-by-step approach | OUP Oxford | 2019 | 9780198841296 | [Library] | |
Set | Carl Edward Rasmussen, Christopher K. I. Williams | Gaussian Processes for Machine Learning | MIT Press | 2006 | 978-0262182539 | [Library] | |
Set | Murphy, K. | Machine Learning: A Probabilistic Perspective | 1st | MIT Press | 2012 | 978-0-262-018029 | [Library] |
CREDIT VALUE | 15 | ECTS VALUE | 7.5 |
---|---|---|---|
PRE-REQUISITE MODULES | ECMM456 |
---|---|
CO-REQUISITE MODULES |
NQF LEVEL (FHEQ) | 7 | AVAILABLE AS DISTANCE LEARNING | No |
---|---|---|---|
ORIGIN DATE | Monday 05 August 2019 | LAST REVISION DATE | Wednesday 18 January 2023 |
KEY WORDS SEARCH | Statistical Modelling |
---|