This module is not currently running in 2024 to 2025.
The curriculum will review the approaches used by natural scientists in the design and analysis of research projects. The principles of experimental design and how these can be applied to field projects will be explained, together with the nature of both quantitative and qualitative data. An introduction to sampling strategies and the role of probability in inferential statistics will lead into the role of descriptive statistics and measures of variability in data exploration. This will be complemented by consideration of the application of both parametric and nonparametric statistics in data analysis (i.e. t-tests, ANOVA, regression, correlation and their nonparametric equivalents), coupled with training in the use of a statistical package to carry out such analyses. Finally, the rules underlying the appropriate presentation of statistical data in research reports will be discussed.
Total contact hours: 30.5
Private study hours: 119.5
Total study hours: 150
MSc Conservation and cognate pathways
Critical Reading (50%): the students are tasked to write a critical response to a scientific article issued by the module convenor in the form of a 'Letter to the Editor'. This critical piece should not exceed 800 words (excluding references)
*This element is pass compulsory and must be passed to achieve the learning outcomes of the module.
Statistical Analysis (50%). This assignment consists of statistical exercises with a series of tasks with clear instructions based on given datasets.
*This element is pass compulsory and must be passed to achieve the learning outcomes of the module.
Reassessment Instrument: 100% coursework.
Dytham, C. 2010. Choosing and Using Statistics: a biologist's guide. 3rd edition. Wiley-Blackwell, Oxford
Folwer, J., Cohen, L. & Jarvis, P. 1998. Practical Statistics for Field Biologists. 2nd edition. Wiley, Chicester
See the library reading list for this module (Canterbury)
On successfully completing the module students will be able to:
1. demonstrate a sound knowledge of the principles of research design and how they should be applied to conservation projects
2. demonstrate a comprehension of the difference between quantitative and qualitative data and the research designs for which each is appropriate
3. understand the use and application of descriptive and inferential statistics in quantitative data analysis
4. demonstrate an appreciation of the use and application of a range of parametric and nonparametric statistical tools in quantitative data analysis
5. use appropriate statistical test to explore and analyse quantitative data
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