Quantitative skills are among the basic and fundamental tools of professional ecologists and biologists. They are necessary to design studies, analyse data, and to assess and interpret published studies. This unit provides a solid grounding in appropriate ways to collect and analyse common types of data in biology and ecology at an intermediate level. It emphasises hands-on, practical experience with widely used statistical software and addresses the common problems often encountered in dealing with biological and ecological data. There is close integration of the lecture and practical components of the unit. The unit covers basic sampling and experimental design, data analysis using standard techniques (e.g. analysis of variance and covariance, regression, analysis of categorical data, generalised linear models), and introduces multivariate techniques for both pattern exploration and hypothesis testing. This unit is strongly recommended for ecology, biology, and environmental science students and those considering Honours. It is suitable for students commencing PhD studies who do not have a strong quantitative background.
|Unit name||Quantitative Methods in Biology|
|College/School||College of Sciences and Engineering
Institute for Marine & Antarctic Studies
|Discipline||College Office - CSE|Ecology and Biodiversity|
|Coordinator||Doctor Nicole Hill|
|Available as an elective?||Yes|
|Delivered By||University of Tasmania|
|Location||Study period||Attendance options||Available to|
- International students
- Domestic students
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|Study Period||Start date||Census date||WW date||End date|
* The Final WW Date is the final date from which you can withdraw from the unit without academic penalty, however you will still incur a financial liability (refer to How do I withdraw from a unit? for more information).
Unit census dates currently displaying for 2024 are indicative and subject to change. Finalised census dates for 2024 will be available from the 1st October 2023. Note census date cutoff is 11.59pm AEST (AEDT during October to March).
- Identify the important features of robust experimental design, assess data characteristics for analysis and interpretation, and describe the strengths and limitations of different approaches to data analysis
- Recognize the characteristics of different kinds of biological and ecological data and the implications of these characteristics for data analysis and interpretation;
- Implement a range of basic statistical techniques relevant to the analysis of biological and ecological data using the R software package
- Apply appropriate statistical techniques commonly used in biology and ecology to analyse univariate data, such as ANOVA, ANCOVA, simple and multivariate regression, logistic and log-linear models and other approaches to categorical data analysis, and GLMs
- Apply appropriate statistical techniques commonly used in biology and ecology to analyse multivariate data, including principal components analysis, cluster analysis, multidimensional scaling, CAP analysis, DISTLM and PERMANOVA
- Interpret and communicate results of statistical techniques relevant to the analysis of biological and ecological data
|Field of Education||Commencing Student Contribution 1,3||Grandfathered Student Contribution 1,3||Approved Pathway Course Student Contribution 2,3||Domestic Full Fee 4|
1 Please refer to more information on student contribution amounts.
2 Please refer to more information on eligibility and Approved Pathway courses.
3 Please refer to more information on eligibility for HECS-HELP.
4 Please refer to more information on eligibility for FEE-HELP.
Please note: international students should refer to What is an indicative Fee? to get an indicative course cost.
Prerequisites(JFA207 OR KMA253) AND (KSM202 OR KZA161 OR KPZ163)
Up to 2-hr online lecture material, 2-hr face to face lectorial, 4-hr face to face practical weekly
|Assessment||Introductory laboratory exercise (5%)|Data analysis and Report (20%)|In-lectorial Quizzes (20%)|Regression & ANOVA Assignment (20%)|Open book exam (35%)|
|Timetable||View the lecture timetable | View the full unit timetable|
There is no compulsory reading for the unit.
However, students will be considerably advantaged by purchasing hard copies of the lecture manual and laboratory manual (available through UniPrint).
The recommended text is Quinn & Keough (2002), but it is not an essential requirement for the unit:
Quinn GP, Keough MK (2002) Experimental design and data analysis for biologists. Cambridge Univ. Press, UK.
Quinn & Keough is one of the most readable and accessible of texts, and it is comprehensive and up-to-date. Above all, it is specifically intended for biologists. For anyone contemplating Honours, or any other form of further study in biology or ecology, this book is strongly recommended.
There is no prescribed reading list. The following is a sample of useful texts and papers that students may find useful to refer to during or after the unit:Textbooks useful for the univariate component of the course:
Rao, P.V. (1998) Statistical Research Methods in the Life Sciences. Duxbury Press, Brooks/Cole, Pacific Grove, California.
Sokal, R.R. & Rohlf, F.J. (1995) Biometry. 3rd ed. W.H. Freeman and Company, San Francisco, CA, U.S.A.
Steel, R.G.D. & Torrie, J.H. (1980) Principles and Procedures of Statistics: a Biometrical Approach. (2nd edition), McGraw-Hill.
Quinn GP, Keough MK (2002) Experimental design and data analysis for biologists. Cambridge Univ. Press, UK. (NOTE: This is the recommended text for this unit).
Textbooks useful for the multivariate component of the course:
Clifford, H.T. and Stephenson, W. (1975). An introduction to numerical classification. Academic Press, New York.
Gauch, H.G. (1982). Multivariate analysis in community ecology. Cambridge University Press.
Green, R.H. (1979). Sampling design and statistical methods for environmental biologists. Wiley, New York.
Legendre, L. and Legendre, P. (1983). Numerical ecology. Elsevier, Amsterdam.
Pielou, E.C. (1984). The interpretation of ecological data. Wiley, New York.
Tabachnick, B.G. & Fidell, L.S. (1996). Using multivariate statistics. 3rd ed., Harper Collins College Publishers, New York, USA.
Williams, W.T. (ed) (1976). Pattern analysis in agricultural sc
|Links||Booktopia textbook finder|
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