Department of Statistics


Planning a MOR

Students who successfully complete a Bachelor of Science (Honours), Bachelor of Arts (Honours), Bachelor of Commerce (Honours), Bachelor of Engineering or Bachelor of Engineering (Honours) with sufficiently high grades and passed some relevant prerequisite courses can progress to a masters degree. Alternatively, you can enter the programme with a Postgraduate Diploma in Operations Research.

Who should study a MOR


The Master of Operations Research is an interfaculty postgraduate degree that enables students with undergraduate backgrounds in Arts, Commerce, Engineering or Science to undertake postgraduate research in Operations Research.

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Structure and prerequisites


The programme provides an opportunity for advanced study in Operations Research through supervised research. It comprises a thesis worth 120 points. To be admitted to this course of study, a student needs to have completed the requirements for the Degrees of BA(Hons), BCom(Hons), BE or BSc(Hons) and passed the prerequisite courses. This degree should be completed in two semesters of full-time study.

Students are expected to negotiate a research topic with their supervisors and undertake relevant background reading before being admitted to the degree.

Prerequisites: BA(Hons), BCom(Hons), BE or BSc(Hons) and the following courses: ENGSCI 760 and ENGSCI 761; or ENGSCI 460 and either ENGSCI 450 or ENGSCI 451

Requirement:


Find more information about the Master of Operations Research:

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Help and advice


If you require assistance and information in planning and guidance in making the best choices for your programme of study contact our Operations Research adviser.

Ilze Ziedins
Phone: +64 9 373 7599 ext 85051
Email: ziedins@stat.auckland.ac.nz

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Meet our graduates


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Kim Frew: Statistician, Harmonic Aotearoa

BSc (Hons) in Statistics (First-Class); BSc (major Pure Mathematics, specialisation in Operations Research); Master of Operations Research (First-Class Honours).

I work with a team of statisticians who assess, design and implement analytical frameworks to help solve business problems. I might be advising clients on data collection methods; data mining to uncover patterns and relationships in datasets; building and monitoring predictive models for clients using techniques such as regression; or doing operations research by investigating innovative ways of achieving efficiency gains and cost savings.

One of the reasons I enjoy statistical work is that there are many potential applications for your skill set. There’s a possibility that you may uncover a pattern, relationship or information that was previously unknown. This insight can help to set a strategy for significant gains in efficiency and cost reduction.

I think there are things about my personality that suit me to statistics. I love problem-solving and knowledge discovery. And there’s an element of creativity in how you apply statistical techniques. It’s fun!

Among the statistics papers I took were STATS125, STATS101, STATS210, STATS255, STATS310, STATS320, STATS325, STATS370 , STATS710, STATS723, STATS731.
 

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Heti Halahuni Afimeimo’unga, Professional Teaching Fellow, Department of Statistics

PhD in Operations Research

I graduated with my PhD, through the Department of Statistics, in May 2012. Operations research is about developing solutions to complex decision-making problems. Take commuting to work, for example: It affects thousands of Kiwis daily and everyone has the same goal – to get to their destination the quickest way possible. So what’s best – choosing a route that’s quickest for the individual, or choosing a route that minimises the overall delay for everyone?

After finishing my PhD, I got a post as a Professional Teaching Fellow in the Department of Statistics. I tutor stage one and two statistics students. I enjoy helping them understand more about statistics and how to understand and analyse data.

I also work as a Tuākana – the word means older sibling or cousin in te reo Māori – which is a programme to help Māori and Pacific students achieve the best possible grades through mentoring, tutorials, workshops and study groups. I tutor the students – in this photo I am standing behind students Ngaian Ah-You (left) and Simon Waigth as they work in the statistics Tuākana room – and also provide data analysis of the Tuākana science students’ pass rates for the Faculty of Science Tuakāna coordinator.

Statistics is part of mathematics, and right from primary school I really liked mathematics. If secondary school students asked me what personal and academic attributes it takes to succeed in a role like mine, I’d say that they have to like helping others. They would need a postgraduate degree at least to be able to teach at university level.

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