STATS 302 : Applied Multivariate Analysis

Science

2025 Semester One (1253) (15 POINTS)

Course Prescription

Covers the exploratory analysis of multivariate data, with emphasis on the use of statistical software and reporting of results. Topics covered include: techniques for data display, dimension reduction and ordination, cluster analysis, multivariate ANOVA and associated methods.

Course Overview

Analysis of data with more than one response variable, including high dimensional cases with hundreds or thousands of responses. The course focuses on the use of R software and the interpretation and presentation of results. Illustrated using data sets from biology, environmental science, finance, sociology, and other areas. This course is suitable for students both majoring in Statistics and those majoring in other fields.  In particular, it is an accessible follow-on from STATS 20x for non-Statistics majors wanting to develop their quantitative skills - particularly those interested in Biology, Ecology, Chemistry, Finance, or Marketing.  

Course Requirements

Prerequisite: ENGSCI 314 or STATS 201 or 208 Restriction: STATS 767

Capabilities Developed in this Course

Capability 3: Knowledge and Practice
Capability 4: Critical Thinking
Capability 5: Solution Seeking
Capability 6: Communication
Graduate Profile: Bachelor of Science

Learning Outcomes

By the end of this course, students will be able to:
  1. Select an appropriate multivariate procedure based on a description of the data and questions of interest, and justify the choice made. (Capability 3, 4 and 5)
  2. Perform correctly the multivariate procedures in a software package, and write justifications for choices made in the course of the analysis. (Capability 3)
  3. Identify the assumptions of their analysis, and means of checking these assumptions. (Capability 3, 4 and 5)
  4. Produce visualisations of multivariate data, including appropriate labels and captions. (Capability 6)
  5. Summarise the conclusions of a multivariate procedure in writing, using non-technical language. (Capability 6)

Assessments

Assessment Type Percentage Classification
Quizzes 10% Individual Coursework
Assignments 20% Individual Coursework
Online Test 20% Individual Coursework
Final Exam 50% Individual Examination
Assessment Type Learning Outcome Addressed
1 2 3 4 5
Quizzes
Assignments
Online Test
Final Exam
50% overall, and 50% in the final exam are required to pass. 

Key Topics

  • Exploratory and descriptive techniques including principal components, canonical variates, clustering, and multidimensional scaling; with associated visualizations
  • Non-Euclidian distances and their uses
  • Inference for differences between groups, and associations between groups of variables, using both permutation testing and parametric methods
  • Methods for dealing with multiple testing including control of the false discovery rate

Special Requirements

The mid semester test will be in the evening. 

Workload Expectations

This course is a standard 15-point course and students are expected to spend 150 hours over the course of the semester for each 15-point course that they are enrolled in.

For this course, a typical weekly workload includes:

  • 3 hours of lectures
  • 3 hours of reviewing the course content
  • 4 hours of work on assignments and/or test preparation

Delivery Mode

Campus Experience

Lectures will be available as recordings. 

Attendance on campus is required for the exam.
The activities for the course are scheduled as a standard weekly timetable.

Learning Resources

Course materials are made available in a learning and collaboration tool called Canvas which also includes reading lists and lecture recordings (where available).

Please remember that the recording of any class on a personal device requires the permission of the instructor.

Coursebook:
  • A pdf of course notes is provided via Canvas

Student Feedback

During the course Class Representatives in each class can take feedback to the staff responsible for the course and staff-student consultative committees.

At the end of the course students will be invited to give feedback on the course and teaching through a tool called SET or Qualtrics. The lecturers and course co-ordinators will consider all feedback.

Your feedback helps to improve the course and its delivery for all students.

 Two improvements that were requested that we will implement in 2025 are 1) starting the course with a "map" of topics to better understand how the different techniques relate to each other, and 2) making more explicit connections to work done in the pre-requisite course, Stats 20x. 

Academic Integrity

The University of Auckland will not tolerate cheating, or assisting others to cheat, and views cheating in coursework, tests and examinations as a serious academic offence. The work that a student submits for grading must be the student's own work, reflecting their learning. Where work from other sources is used, it must be properly acknowledged and referenced. A student's assessed work may be reviewed against electronic source material using computerised detection mechanisms. Upon reasonable request, students may be required to provide an electronic version of their work for computerised review.

Class Representatives

Class representatives are students tasked with representing student issues to departments, faculties, and the wider university. If you have a complaint about this course, please contact your class rep who will know how to raise it in the right channels. See your departmental noticeboard for contact details for your class reps.

Copyright

The content and delivery of content in this course are protected by copyright. Material belonging to others may have been used in this course and copied by and solely for the educational purposes of the University under license.

You may copy the course content for the purposes of private study or research, but you may not upload onto any third party site, make a further copy or sell, alter or further reproduce or distribute any part of the course content to another person.

Inclusive Learning

All students are asked to discuss any impairment related requirements privately, face to face and/or in written form with the course coordinator, lecturer or tutor.

Student Disability Services also provides support for students with a wide range of impairments, both visible and invisible, to succeed and excel at the University. For more information and contact details, please visit the Student Disability Services’ website http://disability.auckland.ac.nz

Special Circumstances

If your ability to complete assessed coursework is affected by illness or other personal circumstances outside of your control, contact a member of teaching staff as soon as possible before the assessment is due.

If your personal circumstances significantly affect your performance, or preparation, for an exam or eligible written test, refer to the University’s aegrotat or compassionate consideration page https://www.auckland.ac.nz/en/students/academic-information/exams-and-final-results/during-exams/aegrotat-and-compassionate-consideration.html.

This should be done as soon as possible and no later than seven days after the affected test or exam date.

Learning Continuity

In the event of an unexpected disruption we undertake to maintain the continuity and standard of teaching and learning in all your courses throughout the year. If there are unexpected disruptions the University has contingency plans to ensure that access to your course continues and your assessment is fair, and not compromised. Some adjustments may need to be made in emergencies. You will be kept fully informed by your course co-ordinator, and if disruption occurs you should refer to the University Website for information about how to proceed.

The delivery mode may change depending on COVID restrictions. Any changes will be communicated through Canvas.

Student Charter and Responsibilities

The Student Charter assumes and acknowledges that students are active participants in the learning process and that they have responsibilities to the institution and the international community of scholars. The University expects that students will act at all times in a way that demonstrates respect for the rights of other students and staff so that the learning environment is both safe and productive. For further information visit Student Charter https://www.auckland.ac.nz/en/students/forms-policies-and-guidelines/student-policies-and-guidelines/student-charter.html.

Disclaimer

Elements of this outline may be subject to change. The latest information about the course will be available for enrolled students in Canvas.

In this course you may be asked to submit your coursework assessments digitally. The University reserves the right to conduct scheduled tests and examinations for this course online or through the use of computers or other electronic devices. Where tests or examinations are conducted online remote invigilation arrangements may be used. The final decision on the completion mode for a test or examination, and remote invigilation arrangements where applicable, will be advised to students at least 10 days prior to the scheduled date of the assessment, or in the case of an examination when the examination timetable is published.