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, in which there are only lower bounds on some data values, multi factor and other generalized linear models, of use when the influences of many factors must be unravelled, data mining techniques, applying when it is desired to search out relationships and last but certainly not least, the principles and consequences of good statistically designed studies.
Learning Outcomes
By the end of the module the student will 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
22522-01 : Raw Module Mark : Coursework (100%)
Assessment Methods & Exceptions
3 hour Written Unseen Examination (80%); In-course Assessment (20%)