The University of Southampton

UOSM2021 More or Less

Module Overview

The module aims to provide a framework for active citizens to understand, manipulate present and respond to the data they encounter every day in news, current affairs, advertising etc.

Aims and Objectives

Module Aims

•Detect misleading uses of statistical data and arguments, e.g. the prosecutor’s fallacy. • Recognize the limits of mathematical and statistical models and apply that knowledge to interpret claims made on the basis of them. • Draw appropriate conclusions from raw data. • Choose appropriate methods to illustrate raw data and support any conclusions.

Learning Outcomes

Learning Outcomes

Having successfully completed this module you will be able to:

  • Intrapersonal skills: the ability to analyse an article as a group and to draw consensual conclusions
  • Critical thinking: the ability to detect and analyse common fallacies and flawed or misleading uses of data
  • Communication skills: the ability to present data and arguments based on data in a meaningful way in a variety of media


Most mathematical/statistical modules for non-mathematicians (eg Mathematics for Engineers) are technical in nature, relatively sophisticated in mathematical terms and technique driven. This module, however, is driven by the use that is made in the media, advertising, politics etc of mathematical/statistical ideas and results. A key first step is critical review. However, we feel that this is necessary but not sufficient. Hence the module also aims to enable students to adapt media reports etc. to incorporate sound mathematical/statistical interpretations that are still suitable for the target audience. This will also allow us to explore the limits of the use of data in journalism and civic life, which we will do with the assistance of experts from the media (see below). How is this module innovative in content? The emphasis on studying current affairs and handling contemporary data from the media distinguishes this module from other methods courses, which tend to focus on controlled situations. On the other hand this module differs from a course in media semiotics in its emphasis on mathematical and statistical interpretation of the claims made by journalists, advertisers, politicians and others.

Special Features

In mathematical modules students may be asked to review material critically or to find solutions to problems, but, particularly in the summative assessment for this module, students will need to combine these aspects

Learning and Teaching

Teaching and learning methods

Each week the class will examine a story from current media or from a bank of case studies to be developed, exploring the claims made within it and the data underlying those claims. Appropriate tools for examining those claims will be introduced and their application will be discussed. Example questions from recent events might include: • An examination of the claims that the breast implants provided by PIP are faulty. (Risks versus likelihood). • An exploration of what the 3 sigma test invoked by physicists in the hunt for the Higgs Boson actually means, and what standards we might apply to test other claims. (Hypothesis testing). • A discussion of the statistics underlying the UCAS data for University admissions over the last three years and the effect of the introduction of fees. (Analysing trends over time). • What does it mean to say that public sector pensions are more generous than private sector schemes? (A discussion of how data types and shapes impinge on summary measures). How is this module innovative in delivery? We will make use of open discussions to expose the (correct and incorrect) use of basic mathematical tools rather than focus on the detail of mathematical methods. The emphasis on contemporary journalism will, we hope, keep the delivery fresh, and the ability to select topics with the class during term will ensure that it is vital and relevant. We have links with the media via the National Cipher Challenge and we will exploit these to get external input from media experts who can give balance to the rather cynical view of the media that this module might otherwise present. The renowned science journalist (and honorary graduate of Southampton University) Simon Singh has agreed to give a lecture in the module on the use of statistics in journalism. Other potential contributors include Tim Harford (presenter of the Radio 4 programme More or Less which inspired this module), Newsnight journalist Mark Urban (with whom we already have links via the National Cipher Challenge) and media alumni including Jon Sopel.

Independent Study114
Total study time150

Resources & Reading list

Others. An archive of recent media stories in which data, statistics or mathematical models are invoked, together with licenses to cover their use in the classroom. Researcher time to analyse the stories in the archive and to prepare briefing notes for them. Access to video and sound recording equipment for student access in order to prepare their own versions of media stories.



MethodPercentage contribution
Coursework 100%


MethodPercentage contribution
Coursework 100%
Share this module Share this on Facebook Share this on Google+ Share this on Twitter Share this on Weibo

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.