Course Details in 2024/25 Session

Module Title	LM Statistical Machine Learning
School	Mathematics
Department	Mathematics
Module Code	06 40206
Module Lead	TBC
Level	Masters Level
Credits	20
Semester	Semester 2
Pre-requisites
Co-requisites
Restrictions	None
Contact Hours	Lecture-48 hours Guided independent study-152 hours Total: 200 hours
Exclusions
Description	This module provides an introduction to a wide range of applicable statistical techniques. A unifying theme is the transferability of statistical ideas. Common features shared by different fields of enquiry enable the development of statistical methodologies with applications throughout Science, Industry and Medicine. Examples from such fields - including the rapidly developing area of Genomics - inform every aspect of the module. Topics covered, which exhibit this transferability, will include: survival analysis; multi factor and other generalized linear models; data mining techniques, applying when it is desired to search out relationships; and the principles and consequences of good statistically designed studies.
Learning Outcomes	By the end of the module students should be able to: Understand statistical association; Plan data collection and analyse data appropriately; Appreciate the use of statistics in various subject areas; Analyse censored data and multi factor data; Appreciate statistical aspects in genomic and data mining.
Assessment
Assessment Methods & Exceptions	Assessment: 80% examination, 20% coursework. Reassessment: Resit exam
Other
Reading List