Key facts
UNE unit code: STAT410
*You are viewing the 2026 version of this unit which may be subject to change in future.
- Trimester 1 - On Campus
- Trimester 1 - Online
- Armidale Campus
- Yes
- No
- Yes
- 6
Unit information
Are you interested in developing and applying statistical models for the natural or social sciences? Do you want to learn more about the principles of designing a data collection? This unit will help you develop the core skills and knowledge needed for experimental designs and applied statistical models that are used in many scientific fields.
Studying this unit, you will learn to develop and analyse various types of linear regression models which are the foundation of many statistical analyses. You will also explore some common experimental designs such as factorial design and randomised block design.
Focusing on both the theoretical and technical aspects of key statistical concepts, topics include multiple linear regression with quantitative and qualitative explanatory variables, polynomial regression and generalised linear models.
Offerings
For further information about UNE's teaching periods, please go to Principal Dates.
| Teaching period | Mode/location |
|---|---|
| Trimester 1 | On Campus, Armidale Campus |
| Trimester 1 | Online |
*Offering is subject to availability
Intensive schools
There are no intensive schools required for this unit.
Enrolment rules
Notes
Three lectures and a one-hour laboratory session per week for on campus students; online students should have access to the statistical package R & RStudio. Students can use Open Source to download R & RStudio. Instructions are given on the unit's Moodle site.
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;
- fit and interpret more complex statistical models, including the linear model;
- build on and broaden their theoretical and technical knowledge of statistical terminology, concepts and methodology to an advanced level, which will enable them to read and critically appraise scientific literature with some confidence; and
- demonstrate a high level of understanding and highly developed communication skills by independently and critically analysing a special topic in advanced regression.
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 |
|---|---|---|---|---|
| Advanced Reading Topic | Yes | 15% | All offerings | Written assessment on Non-parametric Regression. |
| Final Examination - Assurance Task | Yes | 60% | All offerings | Students must achieve a minimum of 50% in the final examination. |
| Quiz 1 | Yes | 2% | All offerings | Online Quiz: Simple Linear Regression and hypothesis testing. Students must complete quiz to access the remaining assessments. |
| Written Assignment 1 | Yes | 3% | All offerings | Written assessment on Multiple Regression. |
| Written Assignment 2 | Yes | 5% | All offerings | Written assessment on Model Building, Variable Screening and Residual Analysis. |
| Written Assignment 3 | Yes | 15% | All offerings | Written assessment on Generalised Linear Models. |
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.
Note: Students are expected to purchase prescribed material. Please note that textbook requirements may vary from one teaching period to the next.
A Second Course in Statistics
ISBN: 9781292042909
Mendenhall, W. and Sincich, T.T., Pearson 7th ed. 2013
Text refers to: All offerings
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