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Unit information: Practical Statistics for Use in Research and Policy in 2019/20

Please note: Due to alternative arrangements for teaching and assessment in place from 18 March 2020 to mitigate against the restrictions in place due to COVID-19, information shown for 2019/20 may not always be accurate.

Please note: you are viewing unit and programme information for a past academic year. Please see the current academic year for up to date information.

Unit name Practical Statistics for Use in Research and Policy
Unit code GEOGM0010
Credit points 20
Level of study M/7
Teaching block(s) Teaching Block 1 (weeks 1 - 12)
Unit director Mr. Hayes
Open unit status Not open
Pre-requisites

N/A

Co-requisites

N/A

School/department School of Geographical Sciences
Faculty Faculty of Science

Description

This course introduces students to concepts and methodologies of social statistics, and how data analysis is used to assess variation in the physical and social world. This course is about quantitative techniques and analysis; looking at how data is collected and issues of survey design; and how data is used in forming policy. At the end of this course, students should: • Understand why we need quantitative methods • Select appropriate analytical techniques (using both descriptive and inferential statistics) • Interpret and analyse quantitative data and output from SPSS (the statistical software we will be using) • Be able to perform and interpret logistic regression • Have an understanding of survey design, sampling, and data collection • Be confident with using and manipulating large-scale datasets • Be able to draw potential policy implications from their own quantitative analysis This is not simply a statistics course – it will give students a good grounding in quantitative methods, data collection, and interpretation and possible policy implications of their findings. Guest lectures will show how statistics are applied in the wider world of industry and the public sector.

Aims: To develop, by debate, discussion, lectures and with hands-on experience, an understanding of key statistical concepts, good practice in the presentation and analysis of social data, awareness of the issues underpinning survey design, and an overview of how to inject geographical thinking into social and environmental data analysis.

Intended learning outcomes

On completing the unit students will be able to demonstrate the following learning outcomes:

  1. a knowledge of the difference between descriptive and inferential statistics;
  2. knowledge of the core ideas and thinking behind inferential statistics;
  3. the ability to perform logistic regression;
  4. an overview of how to inject geographical thinking into statistical research;
  5. an informed and balanced critique of the limits of statistical evidence in social research and policy;
  6. a good understanding of key issues behind survey design;
  7. an understanding of and ability to use SPSS for statistical analysis.

Teaching details

Project-based practical working using SPSS, student presentations.

Assessment Details

There will be two components of the assessment for this course:

1. (Worth 30% of overall mark) – short 1,500 word essay exploring the necessity and advantages of quantitative methods.

2. (Worth 70%) 2,500 word report on a country/area of interest, using data from the World Values Survey. Analysing a key policy area, students will use descriptive and inferential statistical methodologies to infer potential policy implications, in the style of a written report. This will involve data analysis and interpretation; using references from the set readings, and drawing out potential policy implications from their analysis. (A small part (5-10%) of this assessment may come from a provisional presentation on aspects of survey design, that leads into the literature they will be expected to discuss in their main practical).

Reading and References

Rose, D, and Sullivan, O, (various years) Introducing Data Analysis for Social Scientists, Open University Press; any edition.

Bryman, A, 2001, Social Research Methods, Oxford University Press, Oxford.

Ebdon, D, 1985, Statistics in Geography: A Practical Approach, Wiley-Blackwell, Oxford - any edition.

Fotheringham, S, 2006, ‘Quantification, Evidence and Positivism’ in ‘Approaches to Human Geography’ by Aitken and Valentine, Sage – available online/in the library.

Czaja, R, and Blair, J, 1996, Designing Surveys: A Guide to Decisions and Procedures, Pine Forge Press/Sage, London.

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