Data Handling and Statistics 3 is the third applied statistics units offered by the School of Natural Sciences (Mathematics). It provides an extension of the concepts, methods and tools introduced in KMA253. It is a 'hands-on' course in which the emphasis is on the development of skills in the selection and application of upper-level statistical methodology. Emphasis is also placed on the presentation of statistical analyses in a written format that promotes reproducible research. Topics covered in the course include: hypothesis testing, experimental design, inference, analysis presentation, generalised linear modelling; mixed-effects modelling, multinomial regression, and model selection. Expertise with the statistical computing language R and RStudio will be extended, including the application of R Markdown for promoting reproducible research. Examples will be drawn from the biological, physical and social sciences.
|Unit name||Data Handling and Statistics 3|
|Faculty/School||College of Sciences and Engineering
School of Natural Sciences
|Available as student elective?||Yes|
|Location||Study period||Attendance options||Available to|
- International students
- Domestic students
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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.
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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 (see withdrawal dates explained for more information).
|Field of Education||Commencing Student Contribution 1||Grandfathered Student Contribution 1||Approved Pathway Course Student Contribution 2||Domestic Full Fee|
1 Please refer here more information on student contribution amounts.
2 Information on eligibility and Approved Pathway courses can be found here
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 this page to get an indicative course cost.
You cannot enrol in this unit as well as the following:
3 x 1hr face-to-face lectures, 1x1hr tutorial, 1x1-hr computer lab sessions.
3 class tests (46%), projects (54%)
|Timetable||View the lecture timetable | View the full unit timetable|
Fränzi Korner-Nievergelt, Tobias Roth, Stefanie von Felten, Jérôme Guélat, Bettina Almasi, and Pius Korner-Nievergelt (2015) Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and Stan. Academic Press.
Claus Thorn Ekstrom (2017) The R primer. Second edition. CRC Press.
|Links||Booktopia textbook finder|
The University reserves the right to amend or remove courses and unit availabilities, as appropriate.