Course Details in 2025/26 Session


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Module Title LM Statistical Machine Learning
SchoolMathematics
Department Mathematics
Module Code 06 40654
Module Lead Monita Baruah
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