This is an advanced statistical module and students should be comfortable with regression techniques.
OverviewThis module aims to develop students' skills in actively engaging with, critically assessing and communicating quantitative and quantitative 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.
(i) teaching A-level students, and either (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 for then to apply them and present them in a persuasive manner.
This module appears in:
the course will be delivered over 11 weeks, with students receiving at least two hours of contact time per week. While the format of the contact time will vary depending on the topic and also the stage of their group and individual work, it will typically consist of either a 1-hour lecture + 1-hour seminar, or trips/trips to gather, engage and present data to the community.
Method of assessment
100% coursework (50% Report, 40% Group presentation, 10% class participation)
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: 105128.
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)
On successfully completing the module students will be able to:
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;
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;
3 persuasively communicate research results, using empirical research results, both orally, written and through use of images and visualisation across disciplines and audiences;
4 Demonstrate basic data visualisation skills in communicating quantitative research
5 critique how research results are presented in public debates and in academic research;