Research Methods for Biology, Ecology and Zoology (C1021)
15 credits, Level 4
There are certain skills and methods that are essential for being a biologist, ecologist or zoologist. Accurate observation and identification of organisms, and curiosity about them, provides the fuel for scientific discovery.
The use of statistics allows us to test our hypotheses, form a quantitative understanding of experimental and observational data, and draw conclusions based on the information we can extract from them.
Writing and presentation skills are then essential to present our findings in a clear and coherent form so that scientists, policy makers, end-users and the general public can understand them.
This module will help you develop these skills. It will consist of three components:
- an Introduction to Statistics and the use of statistical software to analyse biological and ecological data
- the development of your ability to research and synthesise the primary scientific literature, and communicate your findings
- a series of exercises to develop your observation and identification skills, and scientific curiosity.
Teaching and assessment
We’re currently reviewing teaching and assessment of our modules in light of the COVID-19 situation. We’ll publish the latest information as soon as possible.
Contact hours and workload
This module is approximately 150 hours of work. This breaks down into about 44 hours of contact time and about 106 hours of independent study. The University may make minor variations to the contact hours for operational reasons, including timetabling requirements.
This module is running in the academic year 2021/22. We also plan to offer it in future academic years. However, we are constantly looking to improve and enhance our courses. There may be changes to modules in response to student demand or feedback, changes to staff expertise or updates to our curriculum. We may also need to make changes in response to COVID-19. We’ll make sure to let our applicants know of material changes to modules at the earliest opportunity.
This module is offered on the following courses: