Department of Statistics

Planning a BSc(Hons)

You can enter the Bachelor of Science (Honours) programme after completing a bachelors degree with a major in Statistics. Bridging options are available for students who do not meet this requirement.

Who should study a BSc(Hons)

An honours degree requires a strong background in statistics and is the preferred option for students planning to progress to a masters (MSc or MA) or a PhD in Statistics. It is also useful for students who want to do a PhD overseas and who do not want to complete a masters degree before leaving.


Structure and prerequisites

The honours degree requires one year of full-time study. The degree consists of six postgraduate-level courses plus a research project, worth the equivalent of two courses.

Prerequisite: A major in Statistics and at least 90 points at Stage III and including STATS 210 or 225.


Find more information about the BSc(Hons) in the University Calendar.


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 Honours adviser.

Brendon Brewer

Meet our graduates


Ekaterina Vinkovskaya, Phd student in Statistics, Columbia University, New York

Bachelor of Science in Computer Science and Mathematics, BSc (Honours) in Statistics.

After I graduated, I worked at Westpac as a Risk Analyst. I enjoyed this job a lot!

It involved helping the bank to accurately predict future behaviour and estimate the current behaviour of borrowers to optimise how much money the bank should hold aside to protect itself against defaults.

I applied for a PhD at Columbia for both personal and professional reasons; my parents now live there, and if you want to work in finance, New York is one of the best places to be. Getting into Columbia was challenging every step of the way. I had to spend a week on a practical take-home project and sit three exams of about four hours each. It was a very intense experience.

My research focuses on modelling high-frequency trading in the financial markets. My knowledge of software languages such as SQL, SAS, R, C++ and LATEX serves me well in my doctoral work. I will be graduating in May 2013, and after that I would like to work in finance in New York.

What I treasured about my experience at the University of Auckland was the quality of the collaboration with staff and students in my honours year. The environment was collegial rather than competitive.

University of Auckland statistics graduate Jeff (JieFu) Yu

JieFu Yu, Manager,  Big Data Analytics, Vodfone

BSc (Hons, First Class) in Statistics; Graduate Diploma in Science (Statistics)

My responsibilities include running a high-performance data-science team, driving the company’s big data strategy, leveraging data to deliver our business goals and developing and implementing advanced analytical models.

On a typical day, I talk with stakeholders in New Zealand and overseas, identify data-use cases, ensure that data is available to other parts of the business that need it, and provide support to my data scientists and engineers.

I enjoy finding hidden, vital information in data and using this to give the company strategic advantage. I also really enjoy being involved in strategy formulation. Statistics is an art, just like painting and poetry; it’s all about pattern recognition.

To succeed in this sort of role, you need to have a commercial mind-set, skills in communication and leadership, and a strong knowledge of the field.

I went to the University of Auckland because it’s a top-notch university, and the Department of Statistics is one of the best, with first-class academics throughout. They prepare you for real work situations.

Among the statistics papers I took were Introduction to StatisticsData Analysis for CommerceStatistical TheoryApplied Multivariate AnalysisApplied Time Series AnalysisStatistical Programming and Modeling using SAS, Advanced Statistical ModellingIntroduction to Bayesian StatisticsOfficial StatisticsIntroduction to Medical Statistics and Professional Computing Skills for Statisticians.