| 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 |
| Units you must take before you take this one (pre-requisite units) |
None |
| Units you must take alongside this one (co-requisite units) |
None |
| Units you may not take alongside this one |
None |
| School/department | School of Geographical Sciences |
| Faculty | Faculty of Science |
This course introduces students to concepts and methodologies of social statistics in a digital environment, 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 quantitative analytical methods, including 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
•Present and visualise their analysis appropriately
More widely, students will understand the broader concepts of:
• Data management – handling, management and curating data, including open science principles and practices and discussions of making data and analysis reproducible for other users.
• Recording and representing different modes of data (including textual, aural and visual) considering a range of data visualisation techniques.
• Data analysis – analysing large and complex datasets, and starting to consider coding/ the use of syntax ot enable their 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 (depending on availability) may also 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 analysis and presentation of digitial social data
•awareness of the issues underpinning survey design an overview of how to inject geographical thinking into social and environmental data analysis
• understanding of transferring analysis into impactful, 'real-world', tangible policy outcomes
On completing the unit students will be able to demonstrate the following learning outcomes:
visualisation skills;
how to ensure their work has real-world and tangible outcomes and
policy impacts.
The unit will be taught through a combination of:
hours
There will be two components of the assessment for this course, with one summative assessment at the end of the course:
1. (Formative, though full participation required) - a group presentation exploring the debated necessity and perceived advantages of quantitative methods and their value in the social sciences, particularly when contrasted with qualitative methods.
2. (Worth 100%) Policy Briefing (no more than 2 sides of A4 including references) on a country/area of interest, using data from the World Values Survey. Analysing a key policy area, students will use descriptive and inferential quantitative methodologies to infer potential policy implications, presented in the style of a policy briefing. This will involve data analysis and interpretation using the methods taught in class, independent reading, and drawing out potential policy implications from their analysis, written using non-technical language. Students will also be expected to produce a mandatory technical appendix / supporting document (no more than four sides of A4), presenting the output from their analysis, key
information on coding and decision making, and any ancillary information that they feel may be beneficial to their marks.
If this unit has a Resource List, you will normally find a link to it in the Blackboard area for the unit. Sometimes there will be a separate link for each weekly topic.
If you are unable to access a list through Blackboard, you can also find it via the Resource Lists homepage. Search for the list by the unit name or code (e.g. GEOGM0010).
How much time the unit requires
Each credit equates to 10 hours of total student input. For example a 20 credit unit will take you 200 hours
of study to complete. Your total learning time is made up of contact time, directed learning tasks,
independent learning and assessment activity.
See the University Workload statement relating to this unit for more information.
Assessment
The Board of Examiners will consider all cases where students have failed or not completed the assessments required for credit.
The Board considers each student's outcomes across all the units which contribute to each year's programme of study. For appropriate assessments, if you have self-certificated your absence, you will normally be required to complete it the next time it runs (for assessments at the end of TB1 and TB2 this is usually in the next re-assessment period).
The Board of Examiners will take into account any exceptional circumstances and operates
within the Regulations and Code of Practice for Taught Programmes.
