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Unit information: Convincing stories? Numbers as evidence in the social sciences in 2017/18

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Unit name Convincing stories? Numbers as evidence in the social sciences
Unit code UNIV10002
Credit points 20
Level of study C/4
Teaching block(s) Teaching Block 1 (weeks 1 - 12)
Unit director Professor. Richard Harris
Open unit status Open




School/department School of Geographical Sciences
Faculty Faculty of Science


Quantitative methods are central to social and scientific research, to business and to industry, and knowledge of them is a transferable skill that is attractive in the jobs market. This innovative unit, sponsored by the British Academy, Economic and Social Research Council and the Higher Education Funding Council for England, offers an introduction to quantitative social science, looking at how numbers are used (and abused) to create "stories" in the media, public policy, and in social and scientific debate. The aim of the unit is to prepare students for the sorts of methods and techniques they will encounter in their own discipline by discussing and debating the ideas and concepts that are used to create evidence in an uncertain world, and upon which decisions are made. The unit will encourage students to engage critically with research and debate in their own subject areas, placing them in a better position to learn quantitative skills. This is not a standard "textbook" class on statistics but a class about how and why numbers are used in society, encouraging students to consider how data may be used in their own research and studies. Students who have little or no interest in quantitative methods, who are anxious about mathematics or who simply want to get a head start in their studies are especially welcome on the unit.

Intended learning outcomes

On completing the course, students will:

- have an appreciation of the wide-ranging use of quantitative methods in social and scientific research, and in social and policy debate; - understand the importance of structured form of enquiry to form evidence and knowledge from uncertainty and to help make sense of the real world; - be prepared to"talk back" to a statistic and ask critical questions about how it was created and what it represents; - have knowledge about ideas and concepts such as sampling, probability, measurement, experimentation, causation, randomness and uncertainty; - be better prepared for the sorts of discipline specific methods courses they will encounter in their studies.

Teaching details

Lectures and seminars (face-to-face), supplemented by guided reading. Attendance at classes is mandatory and assessment mark deductions will be made for persistent non-attendance.

Assessment Details

Individual visualisation exercise (40%)

Group Project (60%).

It is intended that the group project will be presented on-line and marked by other students (with marking criteria, quality assurance and a means to appeal provided by and overseen by the academic staff) Attendance at class is also required.

Reading and References

Weekly guided reading will be given.