Courses & Units
Data Analysis Methods QMS517
This unit presents a range of advanced statistical and data analysis techniques used in the marine sciences for students with an existing background in quantitative analysis. The course covers concepts of generalised linear models (GLMs), generalised additive models (GAMs), Bayes rules, bayesian versus frequentist interpretation, Markov chain Monte Carlo fundamentals, hierarchical models, bootstrap, permutation and cross validation tests. An introduction to time series and spectral analysis is given covering correlation, lags, interpolation and filtering techniques, spatial analyis methods (principal component analysis, empirical orthogonal functions, optimal interpolation). The lecture material is complemented by practical sessions using a number of different software packages, such as R, WINBUGS, Python, with exercises using oceanographic, fisheries, and other relevant data sets.
|Unit name||Data Analysis Methods|
|College/School||College of Sciences and Engineering
Institute for Marine & Antarctic Studies
|Discipline||Ecology and Biodiversity|Oceans and Cryosphere|
|Coordinator||Doctor Sophie Bestley|
|Delivered By||University of Tasmania|
This unit is currently unavailable.
Please check that your computer meets the minimum System Requirements if you are attending via Distance/Off-Campus.
Units are offered in attending mode unless otherwise indicated (that is attendance is required at the campus identified). A unit identified as offered by distance, that is there is no requirement for attendance, is identified with a nominal enrolment campus. A unit offered to both attending students and by distance from the same campus is identified as having both modes of study.
* 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 2022 are indicative and subject to change. Finalised census dates for 2022 will be available from the 1st October 2021. Note census date cutoff is 11.59pm AEST (AEDT during October to March).
- You will gain practical knowledge of approaches to statistical modelling of data in a marine and Antarctic context, 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 marine and Antarctic 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 1,3||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.
If you have any questions in relation to the fees, please contact UConnect or more information is available on StudyAssist.
Please note: international students should refer to What is an indicative Fee? to get an indicative course cost.
The unit is a 5-day intensive program with each day consisting of interleaved lecture and practical presentations.
|Assessment||Portfolio (85%)|Portfolio Plan (15%)|
|Timetable||View 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.
No single text covers all the material in this course, but the possible supplemental texts for some topics will be suggested throughout the laboratories.
|Links||Booktopia textbook finder|
The University reserves the right to amend or remove courses and unit availabilities, as appropriate.