Statistics is the language of data and a fundamental tool in all fields of science.  A statistician should be knowledgeable across the entire data pipeline, from modelling systems and experimental design through to data collection and analysis and ultimately to communicating important results.   As we move towards an ever increasingly data-driven society, the statistician's repertoire becomes more and more important.

The lecturers encourage you to ask questions and are always happy to help in a non-judgemental way. Statistics is a key component in so many parts of society, particularly in research. It has prepared me well for my Honours research project.

Dominic Waters - Bachelor of Science (Genetics)

Why Study Statistics at UNE?

Whether you're off campus or living in the picturesque rural environment of Armidale, if you're interested in the interface of data, science, and computing, the University of New England is a great place to study. The statisticians at UNE love scientific modelling especially applied to biology, chemistry, ecology, and education. We're a small group who care about our students and enjoy interacting with them. Our program best serves students with multidisciplinary interests who don't want to get lost in a crowd.

If you want to combine statistics and computing with your love of science, the Computational Science major in the Bachelor of Science may be for you. In this course students learn a common core of computing and statistics, then personalise their degree with at least one area of application. By picking a second major, or choosing from one of our pre-defined themes (in bioinformatics, computational chemistry, applied mathematics and statistics, computational systems biology, precision agriculture, or quantitative ecology), students develop data science skills that set them apart.

If you want to blend statistics with mathematics or have even more of a computing focus, we have other options available. For a greater emphasis on computing, the Applied Modelling (called Data Science from 2017) major in the Bachelor of Computer Science is a great choice. Or, complement a major in Mathematics in the Bachelor of Science with a range of listed units in Statistics.

At the postgraduate level, we offer majors in Statistics (Graduate Certificate in Science) and Applied Statistics (Graduate Diploma in Science), as well as strong statistics offerings in a number of other majors such as Computational Data Science, Quantitative Ecology, Mathematics, and Regulatory Science.


Statistics units may be taken as part of the following courses:

Diploma in Science
Bachelor of Arts/Bachelor of Science
Bachelor of Computer Science
Bachelor of Computer Science/Bachelor of Laws
Bachelor of Science
Bachelor of Science/Bachelor of Laws
Bachelor of Scientific Studies

Graduate Certificate in Science
The Graduate Certificate in Science includes a major in Statistics covering topics such as statistical learning, probability and inference, advanced computational science, statistical modelling and experimental design.

Graduate Diploma in Science
Major in Applied Statistics to study our core statistics units complemented by quantitative offerings across computing, ecology, genetics, and mathematics. Or, if you want to combine quantitative nous with an interest in the natural environment, we offer a multidisciplinary major in Quantitative Ecology. Statistics is also component of several other majors, including Computational Data Science, Mathematics, and Regulatory Science.

Master of Scientific Studies
At the coursework Master's level, we focus on adding value to multidisciplinary majors such as Quantitative Ecology. This major combines a core of statistics and quantitative units in ecology with breadth offerings in areas such as ecological theory, policy, genetics, mathematics, or programming. Statistics units may also be taken in a number of other majors, such as Mathematics, Genetics, or Biodiversity Science.

Postgraduate research
Doctor of Philosophy
Master of Science

Prospective research students are encouraged to contact the Statistics faculty members about possible research projects.


AMTH250 Introduction to Programming in the Sciences
COSC110 Introduction to Programming and the UNIX Environment
COSC120 Object Oriented Programming
COSC220 Software Engineering Studio
COSC370 User Experience and Interaction Design
COSC380 Advanced Computational Science 
GENE352 Genomic Analysis and Bioinformatics 
MTHS120 Calculus and Linear Algebra 1 
MTHS130 Calculus and Linear Algebra 2 
MATH260 Probability and Simulation 
PMTH212 Multivariable Calculus 
PMTH213 Linear Algebra
SCI210 Introduction to Scientific Programming
STAT100 Introduction to Statistical Modelling 
STAT210 Statistical Modelling and Experimental Design 
STAT270 Inference 
STAT320 Advanced Statistical Modelling 
STAT330 Statistical Learning

MATH460 Probability and Simulation 
PMTH412 Multivariable Calculus 
PMTH413 Linear Algebra 
SCI410 Introduction to Scientific Programming 
STAT410 Statistical Modelling and Experimental Design 
STAT420 Advanced Statistical Modelling 
STAT430 Statistical Learning 
STAT470 Inference


Statisticians are in great demand. Starting salaries have remained above the median graduate starting salary for at least the last 25 years. Graduates in Statistics from UNE have found employment in a number of areas: CSIRO, Australian Bureau of Statistics, NRMA, Universities, Survey Companies (eg Gallup
Poll), Banks and Insurance Companies, biotechnology companies, health research units.


Jackie Reid

Jackie's main research focus is in mathematics and statistics education, with a particular interest in the transition to first year tertiary studies for both on- and off-campus students. She is currently the project leader of an OLT grant investigating the development of quantitative skills in the first-year
science curriculum. She has also acted as statistical consultant on a number of ecological and agricultural research projects, including honours projects.

Peter Dillingham

The primary focus of Peter's research is the application and development of statistical methods in ecological and environmental research. This work ranges from developing new chemical sensors to modelling human impacts on animal populations such as seabirds and sharks. He is also interested in the interface of frequentist, Bayesian, and computational methods. The common theme is to use statistics to improve scientific inference, make better decisions in the face of uncertainty, and to develop methods that can be used and understood by scientists.


For information on Statistics at UNE, please contact the Discipline Convenor.