MAT-30014 - Module Specification
School of Computing and Mathematics
Faculty of Natural Sciences

Programme/Approved Electives for 2023/24

Available as a Free Standing Elective

Co-requisites

None

Prerequisites

None

Barred Combinations

None

Description for 2023/24

This module illustrates the application of statistical techniques to health related research. Methods are applied using data from real-life studies, with particular emphasis placed on cancer studies. No prior knowledge of medicine or biology is required. The module commences with a revision of hypothesis testing procedures. This is followed by three main topics: clinical trials, survival analysis and epidemiology. Clinical trials are immensely important for evaluating the relative effectiveness of different treatments, and their design and analysis are considered in-depth. Survival analysis looks at the features and analysis of data from studies of patients with a potentially fatal disease. Epidemiology explores the distribution of disease in a population and discusses studies for assessing whether there is a possible association between a factor (such as, smoking, eating beef, using a mobile phone) and the subsequent development of a disease.
The module develops the following Keele Graduate attributes:
1. An open and questioning approach to ideas, demonstrating curiosity and independence of thought.
2. An appreciation of the development and value of Mathematics and the links between different areas of the subject.
4. The ability creatively to solve problems using a range of different approaches and techniques, and to determine which techniques are appropriate for the problem at hand.
6. The ability to communicate clearly and effectively in written form.

The aim of this module is to study the application of specialised statistical techniques to health related research.

Intended Learning Outcomes

demonstrate knowledge of the concepts of hypothesis testing: 1,2,3,4
demonstrate knowledge of the theory and application of clinical trials: 2,3
demonstrate knowledge of survival analysis, including functions of survival time, comparison of survival distributions, and multivariate techniques: 2,4
demonstrate knowledge of the theory and application of diagnostic testing: 1,2
demonstrate knowledge of systematic review and meta-analysis methodology, and its application: 2
demonstrate knowledge of the science of epidemiology and its applications: 1,2,3,4

Study hours

Lectures: 30 hours
Preparation of coursework: 30 hours
Independent study: 88 hours
Unseen examination : 2 hours

School Rules

None

Description of Module Assessment