Courses & Units

Modelling Biological Data KSM304



Quantitative skills are fundamental to many areas of biology and ecology. With massive increases in the availability of ecological and other kinds of biological data, skill in developing models to describe and understand relationships in data and extrapolate beyond existing data, and an understanding of the nuances of particular kinds of data, is fundamental in modern biological research. This unit builds on the foundation provided in Quantitative Methods in Biology to familiarise students with more advanced model building techniques including generalised linear, mixed and additive models, regression trees, bootstrapping methods, and non-linear regression. The unit will also introduce time series analysis, Bayesian approaches to modelling data, and simulation models including explicitly spatial and individual-based models. It will equip students wanting to understand and/or pursue modern and relevant research in biology and ecology.


Unit name Modelling Biological Data
Unit code KSM304
Credit points 12.5
College/School College of Sciences and Engineering
Institute for Marine & Antarctic Studies
Discipline College Office - CSE|Ecology and Biodiversity
Coordinator Doctor Sophie Bestley
Available as student elective? Yes
Delivered By University of Tasmania
Level Advanced


This unit is currently unavailable.


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Learning Outcomes

  • Aquire practical knowledge of approaches to statistical modelling of biological and ecological data, and key skills in the operation of statistical software packages.
  • Develop the ability to construct statistical models that are fit for purpose, and critically evaluate alternative models in the context of a physical problem.
  • Demonstrate the ability to verbally and graphically communicate the results of statistical analyses clearly and accurately to both technical and non-technical audiences using globally adopted notations and conventions.
  • Understand the role of statistical modelling of biological and ecological data in a range of contexts and applications, and that the application and interpretation of statistical modelling may have important social and ethical implications.
Field of Education Commencing Student Contribution 1 Grandfathered Student Contribution 1 Approved Pathway Course Student Contribution 2 Domestic Full Fee
not applicable

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.

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KSM309 or KMA253


Teaching Pattern

1 semester, 2 x 1 hr lectures, 1 x tutorial and 3 hr practical weekly (13 weeks)

AssessmentExam (30%)|Assignments 1-4 (60%)|Bayesian Scripting (10%)
TimetableView the lecture timetable | View the full unit timetable



There is no compulsory reading for the unit. For some topics supplementary reading material with be provided in addition to the lecture slides, for those that seek a deeper understanding of the material.


 Note that no single text covers all the material in this course, but the books listed below may be of use as additional references. The others will available for short-term loan from the lecturers.

  1. Maindonald, J. and Braun, W.J. (2010). Data analysis and graphics using R. Cambridge University Press
  2. Mattiopoulos, J. (2011). How to be a quantitative ecologist. Wiley,
  3. McElreath, R. (2015) Statistical Rethinking: A Bayesian Course with Examples in R and Stan. CRC Press.
  4. Zuur, A.F, Ieno, E.N, Smith, G.M. (2007). Analysing ecological data. Springer.
LinksBooktopia textbook finder

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