Postgraduate Course: Analysing the Environment (PGGE11198)
|School||School of Geosciences
||College||College of Science and Engineering
|Credit level (Normal year taken)||SCQF Level 11 (Postgraduate)
||Availability||Not available to visiting students
|Summary||This course provides a Master's level introduction to the research approaches and methods that underpin modern social and environmental sciences, with an emphasis on collecting and analysing data. Through a mixture of practicals, group work, lectures and discussion we will explore why and how we do science. The course provides a core set of skills that will be useful in many other courses dealing with empirical science, and in particular is recommended for anyone proposing to conduct a dissertation that involves data collection or analysis. As well as developing skills in qualitative and quantitative data analysis, the associated field course provides an opportunity to build up your group work skills and capacity for professional self-reflection.
The course is actually formed from two 10 credit course (Analysing the Environment and Analysing the Environment Study Tour): in most cases you will have to take both, but for students outwith the MSc Ecosystem Services it may be possible to only take the first course.
In semester one a weekly series of seminars, lectures and practicals introduces the key concepts and methods. This course is assessed through a test and report. The following Easter, a programme-specific fieldtrip provides the opportunity to put the skills you have learned into practice. As part of the field trip you will conduct a group research project, which you will have to present and reflect on.
The course is aimed at those with an undergraduate in either social or natural science. It is introductory in the sense that it assumes no prior experience of either, but quickly moves to Master's level, so prior study in this field is essential.
Week 1. Intro to doing environmental & social sciences: what and why?
Week 2. Designing research
Week 3. Describing and visualising data
Week 4. Analysis of variance
Week 5. Linear regression and correlation
Week 6. Chi-squared tests and non-parametric statistics
Week 7. Doing QUAL social science research
Week 8. Doing QUANT social science research
Week 9. Fieldwork (for assignment 2)
Week 10. Analysis + Writing
Week 11. Creating Impact + Course wrap-up
This course provides an insight and experience of skills sets identified as currently desirable to both the student cohort and employment sector concerned with the wider environment and its study
Entry Requirements (not applicable to Visiting Students)
|| Students MUST have passed:
||Other requirements|| Students MUST be studying on the following programmes to be accepted onto the course: MSc in Ecosystem Services, MSc in Environmental Protection & Management, MSc in Food Security, MSc in Soils & Sustainability.
Students on other programmes may be accepted but MUST request this via the course secretary.
|Additional Costs|| Additional Programme Costs
Course Delivery Information
|Academic year 2016/17, Not available to visiting students (SS1)
|Learning and Teaching activities (Further Info)
Lecture Hours 18,
Seminar/Tutorial Hours 5,
Supervised Practical/Workshop/Studio Hours 5,
Fieldwork Hours 2,
Feedback/Feedforward Hours 2,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
|Assessment (Further Info)
|Additional Information (Assessment)
A1: Testing skills in statistics and data visualisation. Due Fri W7 (40%)
A2: Research report and self-reflection Starts W9 due Monday W12 (60%)
All deadlines are 12:00 unless stated. All assignments must be submitted on Learn only. You work will be marked on Learn and released to you within three weeks (excluding university holidays).
|No Exam Information
On completion of this course, the student will be able to:
- Understand and appreciate that science is not value neutral, and that it is conducted for a variety of reasons and with different beliefs about reality
- Plan for, collect, record and organise qualitative and quantitative data
- Select and then undertake the appropriate type of analysis for a given data set
- Report your results and analysis in a professional manner appropriate for your audience
These resources provide an overview of the course and are important references that you may need to consult. There will also be required reading for each week - see below - and further references will be provided during lectures.
- Required reading:
Gardener, M (2011) Statistics for Ecologists Using R and Excel: Data Collection, Exploration, Analysis and Presentation, Pelagic Publishing. UK. [ebook and hard copy from the university library]
- For students wanting more the theoretical background to the use of statistics, we suggest the following text. It is not required reading however:
Gotelli and Ellison (2012) A Primer Of Ecological Statistics, Sinauer Associates, Inc.; Second edition. [hard copy in library]
Qualitative social science approaches:
- Flowerdew R. & Martin D. (eds) (1997) Methods in human geography. Pearson Prentice Hall. [e-book, library]
- Clifford N. J. & Valentine G. (eds) (2005) Key Methods in Geography. Sage [hard copy, library]
- Silverman D. (2011) Interpreting Qualitative Data. 4th edition. Sage [hard copy, library]
Quantitative social science approaches:
Required reading before each week:
Evely A, et al. (2008) The Influence of Philosophical Perspectives in Integrative Research: a Conservation Case Study in the Cairngorms National Park. Ecology & Society, 13(2), 52.
Pickett, S.T.A., Kolasa, J. & Jones, C.G., 2007. Integration in Ecology. In Ecological Understanding:The Nature of Theory and the Theory of Nature. Elsevier, pp. 3-32. Available at: http://www.sciencedirect.com/science/article/pii/B9780125545228500030
Turner M.D. (2004) Political Ecology and the moral dimensions of "resource conflicts": the case of farmer-herder conflicts in the Sahel. Political Geography, 23(7), 863-889.
Huxham, M. (2000). Science and the search for truth. Chapter 1 in, Huxham, M., and Sumner, D. (eds), Science and Environmental Decision-making, Pearson Educational Ltd., Harlow.
Week 3 - Describing and visualising data
Gardener (2010) Chapters 2-4. In particular, you must make sure you can use R and/or Excel on the University managed desktop machines, or your own laptop.
Week 4 - Analysis of variance
Gardener (2010) Chapter 5, 7, 10.
Week 5 - Linear regression and correlation
Gardener (2010) Chapters 6, 8.
Week 6 - Chi-squared tests and non-parametric statistics
Gardener (2010) Chapters 9.
Rocheleau D. (1995) Maps, Numbers, Text and Context: Mixing Methods in Feminist Political Ecology. Professional Geographer, 47(4), 458-466.
Week 9 (This week will be spent conducting fieldwork i.e. no class or reading)
Crang M. (2005) Analysing Qualitative Materials. In Flowerdew & Martin (Eds.) Methods in Human Geography. A guide for students doing a research project (2nd Edition)
Week 11 (no reading)
|Graduate Attributes and Skills
||1. Organisational skills to plan, execute and report on scientific investigation
2. Use of appropriate computer software (R or Excel) to organise and analyse data
3. Practical experience of collecting data including the use of interviews
4. Interpersonal skills - participating in team activities toward the completion of assignments and goals.
||Yes, for some programmes
|Additional Class Delivery Information
||each 2 hr session is a mixture of lectures and discussion or lab practicals
|Keywords||Data capture,handling,analysis and reporting,dissertation delivery,field skills,statistics.,Epistemo
|Course organiser||Dr Samantha Staddon
|Course secretary||Miss Susie Crocker
Tel: (0131 6)51 7126
© Copyright 2016 The University of Edinburgh - 3 February 2017 4:55 am