Courses & Units
Data Analysis Methods QMS517
Hobart
Introduction
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 primarily using the software package R, with exercises using ecological, oceanographic, fisheries, and other relevant data sets.
Summary
| Unit name | Data Analysis Methods |
|---|---|
| Unit code | QMS517 |
| Credit points | 12.5 |
| College/School | College of Sciences and Engineering Institute for Marine & Antarctic Studies |
| Discipline | Ecology and Biodiversity|Oceans Ice and Climate |
| Coordinator | Doctor Jan Jansen |
| Delivered By | |
| Level | Postgraduate |
Availability
| Location | Study period | Attendance options | Available to | ||
|---|---|---|---|---|---|
| Hobart | Semester 2 | On-Campus | International | Domestic | |
Key
- On-campus
- Off-Campus
- International students
- Domestic students
Note
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Key Dates
| Study Period | Start date | Census date | WW date | End date |
|---|---|---|---|---|
| Semester 2 | 21/7/2025 | 19/8/2025 | 8/9/2025 | 26/10/2025 |
* 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 2025 are indicative and subject to change. Finalised census dates for 2025 will be available from the 1st October 2024. Note census date cutoff is 11.59pm AEST (AEDT during October to March).
Learning Outcomes
- Explain advanced statistical analysis concepts and principles
- Select and apply appropriate data analysis techniques to problems in marine and Antarctic science.
- Critically interpret and report the output of marine and Antarctic science related statistical data analyses.
Fee Information
| Field of Education | Commencing Student Contribution 1,3 | Grandfathered Student Contribution 1,3 | Approved Pathway Course Student Contribution 2,3 | Domestic Full Fee 4 |
|---|---|---|---|---|
| 010103 | $578.00 | $578.00 | not applicable | $2,780.00 |
- Available as a Commonwealth Supported Place
- HECS-HELP is available on this unit, depending on your eligibility3
- FEE-HELP is available on this unit, depending on your eligibility4
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.
Teaching
| Teaching Pattern | The unit is taught as an 8 week semi-intensive, with 4 weeks of face-to-face delivery followed by 4 weeks to complete assessment tasks. The face-to-face period consists of online lectures, in-person workshops and in-person practical presentations twice per week. |
|---|---|
| Assessment | Introductory presentation (10%)|Short report: Test a method (20%)|Quiz (30%)|Main report: Defend a method (40%) |
| Timetable | View the lecture timetable | View the full unit timetable |
Textbooks
| Required |
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. |
|---|---|
| Recommended | No single text covers all the material in this course, but the possible supplemental texts for some topics will be suggested throughout the laboratories. |
The University reserves the right to amend or remove courses and unit availabilities, as appropriate.