STATS 767 : Foundations of Applied Multivariate Analysis

Science

2022 Semester One (1223) (15 POINTS)

Course Prescription

Fundamentals of 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. This course allows postgraduate students to explore this key area of statistics if they have not done so in their undergraduate degree. The course focuses on the use of software and the interpretation and presentation of results. This course includes a project where the student will analyse a dataset of their choice using skills used in this course and prerequisite courses, and prepare written and oral reports. Techniques from the course are particularly key for analysing data from biology, ecology, chemistry, finance, and marketing. 

Course Requirements

Prerequisite: 15 points from BIOSCI 209, STATS 201, 207, 208, 707 Restriction: STATS 302

Capabilities Developed in this Course

Capability 1: Disciplinary Knowledge and Practice
Capability 2: Critical Thinking
Capability 3: Solution Seeking
Capability 4: Communication and Engagement
Graduate Profile: Master 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)
  2. Perform correctly multivariate procedures in a software package, and write justifications for choices made in the course of the analysis. (Capability 1)
  3. Identify the assumptions of their analysis, and means of checking these assumptions. (Capability 2)
  4. Produce visualizations of multivariate data, including appropriate lables and captions, and use them appropriately in written and oral reports. (Capability 4)
  5. Summarise the conclusions of a multivariate procedure orally and in writing, using nontechnical language. (Capability 4)

Assessments

Assessment Type Percentage Classification
Quizzes 5% Individual Coursework
Assignments 20% Individual Coursework
Online Test 15% Individual Coursework
Project 20% Individual Coursework
Final Exam 40% Individual Examination
Assessment Type Learning Outcome Addressed
1 2 3 4 5
Quizzes
Assignments
Online Test
Project
Final Exam

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

Midterm will be the evening of Wednesday 13 April (TBC).

Workload Expectations

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

For this course, in a typical week  you can expect 2 hours of lectures, a 1 hour software lab, 3 hours of reading and thinking about the content and 4 hours of work on assignments and/or test preparation.

Delivery Mode

Campus Experience

(However, this course is suitable for students studying remotely due to COVID).


Lectures will be available as recordings. Other learning activities including zoom office hour will be available as recordings.
The course will include live online events including zoom office hour.
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.

Course book will be provided.

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.

Based on previous comments, we will spend more time discussing the production and interpretation of  the graphs we make in the course. 

The zoom office hour is something students said would be good even in 'normal' circumstances, so we will continue that as long as there is demand. 

Academic Integrity

The University of Auckland will not tolerate cheating, or assisting others to cheat, and views cheating in coursework 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. This requirement also applies to sources on the internet. A student's assessed work may be reviewed against online source material using computerised detection mechanisms.

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 course assessment continues to meet the principles of the University’s assessment policy. Some adjustments may need to be made in emergencies. You will be kept fully informed by your course co-ordinator/director, 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.

Level 1: Delivered normally as specified in delivery mode
Level 2 or higher: You will not be required to attend in person. All teaching and assessment will be delivered remotely.  

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 students may be asked to submit 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. In exceptional circumstances changes to elements of this course may be necessary at short notice. Students enrolled in this course will be informed of any such changes and the reasons for them, as soon as possible, through Canvas.

Published on 25/10/2021 10:21 p.m.