Key facts
UNE unit code: STAT320
*You are viewing the 2027 version of this unit which may be subject to change in future.
- Trimester 2 - On Campus
- Trimester 2 - Online
- Armidale Campus
- Yes
- No
- Yes
- 6
Unit information
In an era of rapid advances in data collection and computational methods, complex data sets are increasingly prevalent. Professionals who can undertake sophisticated statistical modelling to work with these data are vital in many settings.
Build on your statistics foundation and develop skills in advanced regression techniques that will help you to stand out, with this unit.
You will go beyond the linear model, exploring Generalised Linear Models (GLMs), non-linear regression and mixed effects models.
Learning not only how to analyse and interpret complex data, but also how to effectively communicate your results and conclusions, the unit will help you to fine tune invaluable applied skills.
With an approachable blend of theory and hands-on applied exercises, this unit is ideal if you are interested in further developing statistical modelling skills for use in the workplace or academic research.
Offerings
For further information about UNE's teaching periods, please go to Principal Dates.
| Teaching period | Mode/location |
|---|---|
| Trimester 2 | On Campus, Armidale Campus |
| Trimester 2 | Online |
*Offering is subject to availability
Intensive schools
There are no intensive schools required for this unit.
Enrolment rules
Notes
Students must have access to the statistical software R (open source).
Please refer to the student handbook for current details on this unit.
Unit coordinator(s)
Learning outcomes
Upon completion of this unit, students will be able to:
- analyse data, and interpret and communicate results and conclusions, from a wide range of experimental designs;
- use exploratory data analysis to gauge systematic and random components in a data set;
- demonstrate well-developed judgement in the application of advanced models to complex problems;
- fit, assess and interpret advanced statistical models; and
- build on and broaden their theoretical and technical knowledge of statistical terminology, concepts and methodology, which will enable them to read and critically appraise scientific literature with some confidence.
Assessment information
Assessments are subject to change up to 8 weeks prior to the start of the teaching period in which you are undertaking the unit.
| Title | Must Complete | Weight | Offerings | Assessment Notes |
|---|---|---|---|---|
| Assessment 1 | Yes | 10% | All offerings | Data analysis, modelling and report-writing. Must obtain at least 40% for the assignments overall. |
| Assessment 2 | Yes | 15% | All offerings | Data analysis, modelling and report-writing. Must obtain at least 40% for the assignments overall. |
| Assessment 3 | Yes | 15% | All offerings | Data analysis, modelling and report-writing. Must obtain at least 40% for the assignments overall. |
| Final Examination - Assurance Task | Yes | 30% | All offerings | The ProctorU exam includes short answer questions and a data analysis task using RStudio, where students run a model and report their results. To pass, students must obtain: - at least 50% on the combined final and oral examinations - at least 40% for assessments 1 to 3 overall - an overall pass grade |
| Oral Examination - Assurance Task | Yes | 30% | All offerings | To pass, students must obtain: - at least 50% on the combined final and oral examinations - at least 40% for assessments 1 to 3 overall - an overall pass grade |
Learning resources
Textbooks are subject to change up to 8 weeks prior to the start of the teaching period in which you are undertaking the unit.
Textbook information will be displayed approximately 8 weeks prior to the commencement of the teaching period. Please note that textbook requirements may vary from one teaching period to the next.
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