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Biometry (BIOL90002)
Graduate courseworkPoints: 12.5Dual-Delivery (Parkville)
Please refer to the return to campus page for more information on these delivery modes and students who can enrol in each mode based on their location.
About this subject
- Overview
- Eligibility and requirements
- Assessment
- Dates and times
- Further information
- Timetable(opens in new window)
Contact information
July
Overview
| Availability | July - Dual-Delivery |
|---|---|
| Fees | Look up fees |
Biological knowledge is increased by an iterative process of developing ideas, collecting data to assess those ideas, analysing and interpreting those data, and communicating the conclusions. Those conclusions are used to develop new research ideas, improve human health, and to make decisions about environmental management. For this process to be successful, we must collect the right data, enough data, and we must analyse and interpret those data correctly. Biologists must also be able to interpret colleagues’ analyses and interpretation critically.
This subject provides recommendations on appropriate was of collecting data, introduces the most common statistical tools applied to biological (including biomedical and environmental) data, and discusses ways of interpreting and presenting the results of analyses. Topics covered include strategies for efficient and effective estimation, the design of routine monitoring and assessment programs, and experimental design. It will also cover the most common statistical methods used for biological data, including general linear models, logistic and log-linear models, and multivariate techniques, and emphasis will be placed on interpretation and reporting of data analyses.
Intended learning outcomes
At the completion of this subject, students should be able to:
- Demonstrate an understanding of the data generated by biological and environmental research programs;
- Design efficient sampling programs and experiments in biological science;
- Identify biological issues that may cause statistical complications;
- Apply statistical models to different kinds of biological data;
- Present and interpret results of analyses.
Generic skills
At the completion of this subject, students should gain skills in:
- handling, managing and interpreting quantitative data;
- communicating quantitative results to a general audience;
- developing the ability to exercise critical judgement;
- rigorous and independent thinking;
- time management and self-management.
Last updated: 3 November 2022
Eligibility and requirements
Prerequisites
None
Corequisites
None
Non-allowed subjects
None
Recommended background knowledge
Basic understanding of statistical inference, obtained by completion of appropriate undergraduate or postgraduate subjects, or completion of preparatory multimedia material and reading.
Inherent requirements (core participation requirements)
The University of Melbourne is committed to providing students with reasonable adjustments to assessment and participation under the Disability Standards for Education (2005), and the Assessment and Results Policy (MPF1326). Students are expected to meet the core participation requirements for their course. These can be viewed under Entry and Participation Requirements for the course outlines in the Handbook.
Further details on how to seek academic adjustments can be found on the Student Equity and Disability Support website: http://services.unimelb.edu.au/student-equity/home
Last updated: 3 November 2022
Assessment
| Description | Timing | Percentage |
|---|---|---|
A written report, up to 1500 words
| 1 Weeks after the end of teaching | 15% |
A written report, up to 1500 words
| 3 Weeks after the end of teaching | 15% |
A 2 hr written examination - open book
| End of the assessment period | 70% |
Last updated: 3 November 2022
Dates & times
- July
Principal coordinator Allyson O'Brien Coordinator Michael Keough Mode of delivery Dual-Delivery (Parkville) Contact hours 48 hours over eight days, comprising twenty-four 1-hour lectures and eight 3-hour tutorials. Total time commitment 170 hours Teaching period 14 July 2021 to 22 July 2021 Last self-enrol date 15 July 2021 Census date 23 July 2021 Last date to withdraw without fail 6 August 2021 Assessment period ends 22 August 2021 July contact information
Last updated: 3 November 2022
Further information
- Texts
Prescribed texts
Quinn, G.P. & M.J. Keough (2002) Experimental design and data analysis for biologists. Cambridge University Press
Recommended texts and other resources
McCarthy, M.A. (2007) Bayesian methods for ecology. Cambridge University Press
- Subject notes
Students undertaking this subject will be expected to regularly access a computer with statistical software.
- Related Handbook entries
This subject contributes to the following:
Type Name Course Master of Science (BioSciences) Course Bachelor of Agriculture (Degree with Honours) Course Master of Science (Ecosystem Science) Major Tailored Specialisation Major Tailored Specialisation Informal specialisation BioSciences Major Conservation and Restoration Major Conservation and Restoration Informal specialisation Landscape Management Major Sustainable Forests Major Sustainable Forests Major Tailored Specialisation Informal specialisation BioSciences Major Botany - Available through the Community Access Program
About the Community Access Program (CAP)
This subject is available through the Community Access Program (also called Single Subject Studies) which allows you to enrol in single subjects offered by the University of Melbourne, without the commitment required to complete a whole degree.
Entry requirements including prerequisites may apply. Please refer to the CAP applications page for further information.
- Available to Study Abroad and/or Study Exchange Students
This subject is available to students studying at the University from eligible overseas institutions on exchange and study abroad. Students are required to satisfy any listed requirements, such as pre- and co-requisites, for enrolment in the subject.
Last updated: 3 November 2022