How to Win Arguments with Numbers - SOCI7460

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Module delivery information

This module is not currently running in 2024 to 2025.

Overview

This module aims to develop students' skills in actively engaging with, critically assessing and communicating quantitative and qualitative research to a range of different audiences both within and outside of the realms of academia. Students will actively develop skills in explaining and visualising research and will also reflect on the challenges in communicating research and also on how research is used in practice and policy.

• The first part of the module will focus on giving students the basic understanding of how and when to make use of a range of data
visualisation tools, how to construct arguments both in writing and orally as well as how to assess how others communicate and carry out
research.
• The second part of the module will focus on applying these skills by creating both a group presentation and an individual report where
students make use of the skills learnt in the first part.
• Students will develop these skills by working in groups where they are asked to use quantitative data and to communicate results by either
(i) teaching A-level students, (ii) setting up a public event, or (iii) producing a short TV/radio feature using secondary data for substantive
topics on e.g. single parenthood. This means that part of the module will include engaging with a range of audiences to shape relevant
projects focusing on topics that are important to the particular audience students are working with. The latter meaning that students will
apply their acquired skills in interpreting and choosing data, and presenting it in a persuasive manner.

Details

Contact hours

Total contact hours: 22
Private study hours: 128
Total study hours: 150

Availability

BSc Statistical Social Research
Any programme that includes 'with Quantitative Research'
Also available as a 'wild' module

Method of assessment

Main assessment methods

Report (2500 words) (50%)
Group Presentation (40%)
Class Participation (10%)

Reassessment methods

Reassessment Instrument: 100% coursework

Indicative reading

Buroway, M (2004/2005), 'For public sociology [2004 American Sociological Association Presidential Address]'. British Journal of Sociology, 56(2):259-294. DOI: 10.1111/j.1468-4446.2005.00059.x.
Cleveland, William S. 1993. Visualizing Data, Hobart Press, Summit, NJ.
Few S. 2009. Now You See It: Simple Visualization Techniques for Quantitative Analysis. Oakland, CA: Analytics
Few S. 2012. Show Me the Numbers: Designing Tables and Graphs to Enlighten. Burlingame, CA: Analytics. 2nd ed.
Healy, K. and Moody, J. (2014). Data visualization in Sociology', Annual Review of Sociology, 40: 105–128.
Oreskes, N. (2004) 'Science and Public Policy: What's Proof Got to Do with It?' Environmental Science & Policy 7:369-83.
Tufte, Edward. 2001. The Visual Display of Quantitative Information, 2nd edition, Graphics Press, Cheshire, CT. (First edition 1983)

See the library reading list for this module (Canterbury)

Learning outcomes

The intended subject specific learning outcomes.
On successfully completing the module students will be able to:

8.1 Demonstrate ability to make persuasive arguments using quantitative research, and to critically assess the arguments made by others in
the course of social life;
8.2 Demonstrate skills in understanding how to choose and interpret research results, and to assess the quality and strength of both
quantitative and qualitative research;
8.3 Persuasively communicate research results, using empirical research results, both orally, written and through use of images and
visualisation across disciplines and audiences;
8.4 Demonstrate basic data visualisation skills in communicating quantitative research
8.5 Critique how research results are presented in public debates and in academic research.

The intended generic learning outcomes.
On successfully completing the module students will be able to:

9.1 Demonstrate a basic ability to use, analyse and present advanced quantitative data;
9.2 Understand the strengths and weaknesses of advanced quantitative methods of causal analysis, and apply sound judgement in real-world
scenarios;
9.3 Organise information clearly and persuasively communicate research in oral and written form to a range of audiences;
9.4 Create visualisations and presentations of complex data by use of software;
9.5 Work in a group and to produce clear communication of research results as a team.

Notes

  1. ECTS credits are recognised throughout the EU and allow you to transfer credit easily from one university to another.
  2. The named convenor is the convenor for the current academic session.
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