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Statistics● OpenMastersPreview

Master of Applied Statistics

Advance your career by mastering practical statistical techniques and data analysis at Victoria University of Wellington.

Best for:Best for bachelor's graduates in quantitative fields seeking practical data analysis and professional statistical training.

Victoria University of Wellington · Wellington, New Zealand · R1 · First-stage researcher
More professors at Victoria University of Wellington
applied statisticsdata analysisstatistical modelingquantitative methods
This is a masters position — not a PhD studentship.
Deadline
—
Funding
—
1.48 years
Start date
2027-02-22
Location
Wellington
New Zealand

Overview

The Master of Applied Statistics (MAppStat) at Victoria University of Wellington is a professional postgraduate programme designed to equip students with practical data analysis and statistical modeling skills. Blending rigorous coursework with hands-on professional training, the curriculum prepares graduates to meet the high demand for data interpretation across industries. Students explore advanced statistical techniques and engage with real-world applications to build a strong foundation for analytical careers. The programme serves as an ideal pathway for bachelor's graduates aiming to step into professional roles that require turning complex data into actionable insights.

Master of Applied Statisticspostgraduate studydata analyticsstatistical techniquesprofessional trainingVictoria University of Wellington

What you'll do

  • Complete rigorous coursework in advanced statistical methods and techniques
  • Participate in hands-on practical training and data analysis projects
  • Apply computational and quantitative tools to interpret large datasets
  • Engage with varied professional workflows and applied industry challenges

Requirements

Degree required: Bachelor's degree in a relevant field

Degree offered: Master of Applied Statistics

Language: English; standard university English language entry requirements apply

Instruction: English

Required skills
  • Foundational knowledge in mathematics or statistics from prior undergraduate studies
  • Quantitative problem-solving abilities
  • Analytical aptitude for handling numerical data
Nice to have
Prior coursework in statistics, calculus, or linear algebraBasic programming experience in R, Python, or similar statistical software
Eligibility
  • Hold an approved Bachelor's degree or equivalent qualification

Funding & terms

Type
Unknown
Amount
—
Duration
1.48 years
Programme
—

Programme and admissions

Admissions not verified

A catalogue listing does not mean applications are open or funding is guaranteed. Check the source for your intake.

Intake
Not confirmed by the source
Duration
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Teaching language
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Taught / research mode
Not confirmed by the source
Study mode
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Campus
Not confirmed by the source
Prerequisites
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Application instructions
Not confirmed by the source
Tuition
Not confirmed by the source
Funding
Not confirmed by the source

How to apply

Interested applicants should review the course details on the official university admissions portal and submit their application along with the necessary academic documentation before the intake date.

Documents required
  • Bachelor's degree transcripts
  • Proof of identity
  • English language proficiency test scores if applicable
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Check admissions, intake and funding with the official source; a listing does not mean applications are open.