Statistical literacy and data collection. Descriptive statistics and the interpretation of data, probability, random variables and probability distributions, sampling and estimation, hypothesis testing, correlation and regression, use of R software.

Course code

Qualifications are made up of courses. Some universities call these papers. Each course is numbered using six digits.



The fourth number of the course code shows the level of the course. For example, in course 219206, the fourth number is a 2, so it is a 200-level course (usually studied in the second year of full-time study).



Each course is worth a number of credits. You combine courses (credits) to meet the total number of credits needed for your qualification.


Course planning information

Course notes

161.122 takes an in-depth approach to statistics with a strong focus on computing. It allows entry into all 200-level statistics courses. Students without a strong computing or mathematical background should consider 161.111 Applied Statistics which covers key statistical concepts in an accessible way.

Expected prior learning

At least 16 credits in NCEA Level 3 Mathematics from these standards: 91573, 91574, 91575, 91576, 91577, 91578, 91579, 91587;
passed any 100-level mathematics course (prefix 160) except 160.104.

If you do not have this prior learning or equivalent you should enrol in this Massey University course instead:
160.105 Methods of Mathematics

If it is some time since you studied Mathematics at school, you can find out if you have the expected background by taking this maths quiz..


Choose just one

The courses listed above have similar content to this one meaning you can only enrol in this course or one of the listed courses. Only one of the courses can be credited towards your qualification.

Learning outcomes

What you will learn. Knowledge, skills and attitudes you’ll be able to show as a result of successfully finishing this course.

  • 1 Plan the collection of data for a specific purpose from appropriate data sources, and critique a given data collection scheme.
  • 2 Choose appropriate software techniques for summarising and visualising complex datasets, communicating the results in context.
  • 3 Analyse and interpret relationships between variables.
  • 4 Use a range of probability models and their characteristics to make predictions for random variables.
  • 5 Construct and interpret confidence intervals for a range of population parameters.
  • 6 Apply the theory of hypothesis testing to construct and critique inferential statements about population characteristics, as part of the scientific method.

Learning outcomes can change before the start of the semester you are studying the course in.


Assessment Learning outcomes assessed Weighting
Written Assignment 1 2 3 10%
Written Assignment 1 2 3 4 5 10%
Written Assignment 1 2 3 4 5 6 10%
Test 1 2 3 4 5 6 20%
Exam College/GRS-based (not centrally scheduled) 1 3 4 5 6 50%

Assessment weightings can change up to the start of the semester the course is delivered in.

You may need to take more assessments depending on where, how, and when you choose to take this course.

Explanation of assessment types

Computer programmes
Computer animation and screening, design, programming, models and other computer work.
Creative compositions
Animations, films, models, textiles, websites, and other compositions.
Exam College or GRS-based (not centrally scheduled)
An exam scheduled by a college or the Graduate Research School (GRS). The exam could be online, oral, field, practical skills, written exams or another format.
Exam (centrally scheduled)
An exam scheduled by Assessment Services (centrally) – you’ll usually be told when and where the exam is through the student portal.
Oral or performance or presentation
Debates, demonstrations, exhibitions, interviews, oral proposals, role play, speech and other performances or presentations.
You may be assessed on your participation in activities such as online fora, laboratories, debates, tutorials, exercises, seminars, and so on.
Creative, learning, online, narrative, photographic, written, and other portfolios.
Practical or placement
Field trips, field work, placements, seminars, workshops, voluntary work, and other activities.
Technology-based or experience-based simulations.
Laboratory, online, multi-choice, short answer, spoken, and other tests – arranged by the school.
Written assignment
Essays, group or individual projects, proposals, reports, reviews, writing exercises, and other written assignments.