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Applied Statistics for Biologists (BIOL90002)
Graduate courseworkPoints: 12.5On Campus (Parkville)
About this subject
- Overview
- Eligibility and requirements
- Assessment
- Dates and times
- Further information
- Timetable (login required)(opens in new window)
Contact information
Overview
| Availability | Semester 1 |
|---|---|
| Fees | Look up fees |
This subject focuses on common statistical approaches used to analyse biological data sets. Topics covered include research and experimental design, hypothesis testing, estimation, and statistical modelling for univariate and multivariate data. In interactive classes, students will consolidate concepts before working through examples in the context of different disciplines within the biosciences (including biomedicine, genetics, environmental science and ecology). The computer-based workshops will provide opportunities to translate theoretical knowledge into practice with emphasis on statistical interpretation, reasoning, and basic coding skills. By the end of the subject, students will have the statistical skills required to design, analyse, and interpret their own biological research.
Intended learning outcomes
At the completion of this subject, students should be able to:
- apply appropriate statistical models to biological and environmental data sets;
- explain how good experimental design facilitates effective statistical tests;
- use basic coding within the R statistical environment;
- evaluate a research design and statistical methodology published in scientific literature; and
- justify their own statistical decisions and experimental designs.
Generic skills
On completion of this subject students should have developed the following generic skills:
- data management skills: ability to implement appropriate data and information management protocols,
- analytical skills: ability to apply quantitative inference and reasoning,
- problem solving skills: capacity to solve statistical problems faced by research biologists,
- critical thinking skills: capacity to demonstrate independent critical thinking; and
- time management skills: ability to manage study time and learning independently.
Last updated: 31 January 2024
Eligibility and requirements
Prerequisites
Corequisites
Non-allowed subjects
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: 31 January 2024
Assessment
| Description | Timing | Percentage |
|---|---|---|
Four in-class quizzes (5% each) based on concepts from interactive classes, spaced evenly across the semester.
| Weeks 2, 4, 7, 11 | 20% |
Two coding assignments (equivalent to 600 words each) associated with computer-based workshops
| Weeks 3-4 and 9-10 | 30% |
A critical review
| From Week 6 to Week 7 | 15% |
A final synthesis report
| During the assessment period | 35% |
Last updated: 31 January 2024
Dates & times
- Semester 1
Coordinator Allyson O'Brien Mode of delivery On Campus (Parkville) Contact hours Total time commitment 170 hours Teaching period 26 February 2024 to 26 May 2024 Last self-enrol date 8 March 2024 Census date 3 April 2024 Last date to withdraw without fail 3 May 2024 Assessment period ends 21 June 2024
What do these dates mean
Visit this webpage to find out about these key dates, including how they impact on:
- Your tuition fees, academic transcript and statements.
- And for Commonwealth Supported students, your:
- Student Learning Entitlement. This applies to all students enrolled in a Commonwealth Supported Place (CSP).
Subjects withdrawn after the census date (including up to the ‘last day to withdraw without fail’) count toward the Student Learning Entitlement.
Last updated: 31 January 2024
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 (Ecosystem Science) Course Bachelor of Agriculture (Degree with Honours) Course Master of Science (BioSciences) Major Conservation and Restoration Major Conservation and Restoration Major Botany Major Tailored Specialisation Major Sustainable Forests Major Sustainable Forests Major Tailored Specialisation Major Tailored Specialisation Informal specialisation Landscape Management Informal specialisation BioSciences Informal specialisation BioSciences - 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: 31 January 2024